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ReadMe Revamp (#156)
* HF Perf Button * Update README.md Adding new buttons cleanup * Update README.md * Delete images/Discord.png * Delete images/try live demo green.png * new transparent logos * Revamping page * Revamp mainpage * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * finetune button * Delete start free finetune button.png * free finetune button * Add files via upload * Update README.md * Update README.md * Add files via upload * Add files via upload * Update README.md * Add files via upload * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Squashed commit of the following: commitefa0d2332eAuthor: Daniel Han <danielhanchen@gmail.com> Date: Sun Feb 4 17:35:56 2024 +1100 2x faster inference (#151) * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py * Works? * Update pyproject.toml * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Swiglu * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * attention_mask * Update llama.py * Update llama.py * labels * Update mistral.py * Update llama.py * attention mask * Update save.py * Update save.py * Update mistral.py * attention mask * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update dpo.py * Patch saving * Update save.py * Update save.py * patch_saving_functions * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * print * Mistral patch * Update mistral.py * Update save.py * saving * Update llama.py * Update llama.py * Fast inference repatch * Update llama.py * Update utils.py * Update utils.py * Update utils.py * Update mistral.py * Update __init__.py * Fix inference * Update mistral.py * fast lm_head * Remove fast path * Update rope_embedding.py * Update loader.py * LlamaAttention_fast_forward_inference * if past_key_value is not None and q_len == 1: * revert inference * Update loader.py * past_key_value * Update llama.py * Update llama.py * Fix SDPA * Update llama.py * padding * Inference * Update llama.py * Revert * Update mistral.py * faster inference * inference * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * inference * Update llama.py * Update utils.py * faster inference * Update llama.py * revert * lm_head * Update llama.py * inference * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * faster inference * Update llama.py * fast inference * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * torch compile * past_key_values * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update utils.py * Update utils.py * Update utils.py * Update utils.py * Update llama.py * fast inference + saving config.json * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * fast inference again * more temp matrices * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update mistral.py * Update llama.py * SDPA * attention_mask * New version * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update utils.py * Update utils.py commit2f55935f94Author: Daniel Han <danielhanchen@gmail.com> Date: Wed Jan 31 04:03:37 2024 +1100 Hotfix - fix inference (#146) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py * Works? * Update pyproject.toml * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Swiglu * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * attention_mask * Update llama.py * Update llama.py * labels * Update mistral.py * Update llama.py * attention mask * Update save.py * Update save.py * Update mistral.py * attention mask * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update dpo.py * Patch saving * Update save.py * Update save.py * patch_saving_functions * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * print * Mistral patch * Update mistral.py * Update save.py * saving * Update llama.py * Update llama.py * Fast inference repatch * Update llama.py * Update utils.py * Update utils.py * Update utils.py * Update mistral.py * Update __init__.py * Fix inference * Update mistral.py * fast lm_head * Remove fast path * Update rope_embedding.py * Update loader.py * LlamaAttention_fast_forward_inference * if past_key_value is not None and q_len == 1: * revert inference * Update loader.py * past_key_value commita3a2ad9382Author: Daniel Han <danielhanchen@gmail.com> Date: Mon Jan 29 17:49:54 2024 +1100 Fix inference attention mask (#142) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py * Works? * Update pyproject.toml * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Swiglu * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * attention_mask * Update llama.py * Update llama.py * labels * Update mistral.py * Update llama.py * attention mask * Update save.py * Update save.py * Update mistral.py * attention mask * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update dpo.py * Patch saving * Update save.py * Update save.py * patch_saving_functions * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * print * Mistral patch * Update mistral.py * Update save.py * saving * Update llama.py * Update llama.py commit90309ca8dcAuthor: Daniel Han <danielhanchen@gmail.com> Date: Mon Jan 29 03:45:07 2024 +1100 Nightly (#140) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py * Works? * Update pyproject.toml * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Swiglu * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * attention_mask * Update llama.py * Update llama.py * labels * Update mistral.py * Update llama.py * attention mask * Update save.py * Update save.py * Update mistral.py * attention mask * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update dpo.py * Patch saving * Update save.py * Update save.py * patch_saving_functions * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * print * Mistral patch * Update mistral.py * Update save.py * saving commita16bc73e80Author: Daniel Han <danielhanchen@gmail.com> Date: Mon Jan 29 02:52:39 2024 +1100 Fix saving issues (#139) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py * Works? * Update pyproject.toml * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Swiglu * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * attention_mask * Update llama.py * Update llama.py * labels * Update mistral.py * Update llama.py * attention mask * Update save.py * Update save.py * Update mistral.py * attention mask * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update dpo.py * Patch saving * Update save.py * Update save.py * patch_saving_functions * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * print commitaf33224554Author: Daniel Han <danielhanchen@gmail.com> Date: Sun Jan 28 04:30:29 2024 +1100 1 more bug (#138) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py * Works? * Update pyproject.toml * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Swiglu * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * attention_mask * Update llama.py * Update llama.py * labels * Update mistral.py * Update llama.py * attention mask * Update save.py * Update save.py commite2bbd3819eAuthor: Daniel Han <danielhanchen@gmail.com> Date: Sun Jan 28 04:20:06 2024 +1100 Fix bugs + more accurate Swiglu (#137) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py * Works? * Update pyproject.toml * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Swiglu * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * attention_mask * Update llama.py * Update llama.py * labels * Update mistral.py * Update llama.py * attention mask commita81aff286fAuthor: Daniel Han <danielhanchen@gmail.com> Date: Sat Jan 27 04:50:22 2024 +1100 Inference bug fix (#134) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Revert "Update llama.py" This reverts commita208ec46e0. * Update llama.py commit7da0c50f75Author: Daniel Han <danielhanchen@gmail.com> Date: Sat Jan 27 04:47:54 2024 +1100 More bug fixes (#133) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update swiglu.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update fast_lora.py * Update save.py * Update fast_lora.py * Update utils.py * Update llama.py * Update fast_lora.py * Update swiglu.py * Update save.py * Update save.py * Update llama.py * Update llama.py * Update llama.py commit62fae3aa74Author: Daniel Han <danielhanchen@gmail.com> Date: Fri Jan 26 04:19:17 2024 +1100 Fix bugs (#129) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving * Update llama.py * hidden_states * q_len == 1 * q_len issue * Update mistral.py * Update mistral.py * incorrect inference * Update to transformers 4.37 * Graceful FA2 error + torch 2.1.1 * Update mapper.py * Update pyproject.toml * Fix saving and bnb-4bit * Update fast_lora.py * Update fast_lora.py * remove patching * Update llama.py * Update llama.py * Update swiglu.py * Repatch * Update fast_lora.py commit04f8771821Author: Daniel Han <danielhanchen@gmail.com> Date: Tue Jan 23 03:55:24 2024 +1100 2-4x faster native HF inference (#119) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * fast inference * Update llama.py * Update save.py * Update llama.py * Mistral correct RoPE scaling * Max sequence lengths * Apache 2 * fast_linear_forward * Update utils.py * Update utils.py * No print * Update utils.py * Update utils.py * inference * Update llama.py * Fast inference RoPE * Update llama.py * Update llama.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * LoRA * Fast LoRA saving commit3a9b2dee98Author: Daniel Han <danielhanchen@gmail.com> Date: Sun Jan 21 22:20:22 2024 +1100 Hotfix (#118) * faster saving & inference * Update llama.py * Update save.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update mistral.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py commita6f4fb0075Author: Daniel Han-Chen <danielhanchen@gmail.com> Date: Sun Jan 21 05:00:37 2024 +1100 Update save.py commit705cac0357Author: Daniel Han-Chen <danielhanchen@gmail.com> Date: Sun Jan 21 04:21:54 2024 +1100 Update save.py commit16edcb3be2Author: Daniel Han-Chen <danielhanchen@gmail.com> Date: Sun Jan 21 04:13:03 2024 +1100 Update save.py commit3d05a74b12Author: Daniel Han <danielhanchen@gmail.com> Date: Sun Jan 21 03:43:49 2024 +1100 Fixed saving! (#113) * Fix tokenizer, dropout, bias for LoRA * Update loader.py * Fix LoRA downcasting * Update _utils.py * Saving to GGUF * fix * colab_quantize_to_gguf * move save modules * save module * Update __init__.py * Update save.py * Temp downgrade due to TRL issue * Fix up bugs * Faster saving + other changes * Update llama.py * Saving modules * spelling * Update llama.py * Update save.py * Update save.py * Update loader.py * Update llama.py * patch saving * Update save.py * Update save.py * Update save.py * patch saving * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * original_model * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * saving to RAM leakage? * Update save.py * new_save_directory * Update save.py * Update save.py * Update save.py * Update save.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Quick fixes * Update llama.py * Update llama.py * Update dpo.py * Update dpo.py * Update llama.py * Update save.py * getattr * RSLoRA and LoftQ direct support * Update llama.py * Update llama.py * Update llama.py * Fix DPO + GGUF * Fix quantization_method * Fix quantization_config * patch model * Update llama.py * Update llama.py * Update llama.py * Update save.py * Update save.py * tokenizer_save_settings * Update save.py * quantization and loftq * Update save.py * Update llama.py * Update save.py * upload_to_huggingface * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py commitbb05d6b6e2Author: Daniel Han <danielhanchen@gmail.com> Date: Sat Jan 20 23:23:00 2024 +1100 Hotfix for Jan 2024 Release (#110) * Fix tokenizer, dropout, bias for LoRA * Update loader.py * Fix LoRA downcasting * Update _utils.py * Saving to GGUF * fix * colab_quantize_to_gguf * move save modules * save module * Update __init__.py * Update save.py * Temp downgrade due to TRL issue * Fix up bugs * Faster saving + other changes * Update llama.py * Saving modules * spelling * Update llama.py * Update save.py * Update save.py * Update loader.py * Update llama.py * patch saving * Update save.py * Update save.py * Update save.py * patch saving * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * original_model * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * saving to RAM leakage? * Update save.py * new_save_directory * Update save.py * Update save.py * Update save.py * Update save.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Quick fixes * Update llama.py * Update llama.py * Update dpo.py * Update dpo.py * Update llama.py * Update save.py * getattr * RSLoRA and LoftQ direct support * Update llama.py * Update llama.py * Update llama.py * Fix DPO + GGUF * Fix quantization_method * Fix quantization_config * patch model * Update llama.py * Update llama.py * Update llama.py * Update save.py * Update save.py * tokenizer_save_settings * Update save.py * quantization and loftq * Update save.py * Update llama.py * Update save.py commit12e75c93d0Author: Daniel Han <danielhanchen@gmail.com> Date: Sat Jan 20 04:25:06 2024 +1100 Quick fixes (#106) * Fix tokenizer, dropout, bias for LoRA * Update loader.py * Fix LoRA downcasting * Update _utils.py * Saving to GGUF * fix * colab_quantize_to_gguf * move save modules * save module * Update __init__.py * Update save.py * Temp downgrade due to TRL issue * Fix up bugs * Faster saving + other changes * Update llama.py * Saving modules * spelling * Update llama.py * Update save.py * Update save.py * Update loader.py * Update llama.py * patch saving * Update save.py * Update save.py * Update save.py * patch saving * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * original_model * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * saving to RAM leakage? * Update save.py * new_save_directory * Update save.py * Update save.py * Update save.py * Update save.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Quick fixes * Update llama.py * Update llama.py * Update dpo.py * Update dpo.py * Update llama.py * Update save.py * getattr * RSLoRA and LoftQ direct support * Update llama.py * Update llama.py * Update llama.py * Fix DPO + GGUF commit52b5ef31e0Author: Daniel Han-Chen <danielhanchen@gmail.com> Date: Sat Jan 20 02:30:31 2024 +1100 Update _utils.py commit1a19c38675Merge:0a523900d6e52bAuthor: Daniel Han-Chen <danielhanchen@gmail.com> Date: Fri Jan 19 23:15:38 2024 +1100 Merge branch 'main' of https://github.com/unslothai/unsloth commit0a52390ac2Author: Daniel Han-Chen <danielhanchen@gmail.com> Date: Fri Jan 19 23:15:20 2024 +1100 Revert quantization methods commit0d6e52b5c7Author: Daniel Han <danielhanchen@gmail.com> Date: Fri Jan 19 22:57:22 2024 +1100 getattr issues (#103) * Fix tokenizer, dropout, bias for LoRA * Update loader.py * Fix LoRA downcasting * Update _utils.py * Saving to GGUF * fix * colab_quantize_to_gguf * move save modules * save module * Update __init__.py * Update save.py * Temp downgrade due to TRL issue * Fix up bugs * Faster saving + other changes * Update llama.py * Saving modules * spelling * Update llama.py * Update save.py * Update save.py * Update loader.py * Update llama.py * patch saving * Update save.py * Update save.py * Update save.py * patch saving * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * original_model * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * saving to RAM leakage? * Update save.py * new_save_directory * Update save.py * Update save.py * Update save.py * Update save.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Quick fixes * Update llama.py * Update llama.py * Update dpo.py * Update dpo.py * Update llama.py * Update save.py * getattr commitb3fcea6421Author: Daniel Han <danielhanchen@gmail.com> Date: Fri Jan 19 22:52:30 2024 +1100 Quick fixes (#101) * Fix tokenizer, dropout, bias for LoRA * Update loader.py * Fix LoRA downcasting * Update _utils.py * Saving to GGUF * fix * colab_quantize_to_gguf * move save modules * save module * Update __init__.py * Update save.py * Temp downgrade due to TRL issue * Fix up bugs * Faster saving + other changes * Update llama.py * Saving modules * spelling * Update llama.py * Update save.py * Update save.py * Update loader.py * Update llama.py * patch saving * Update save.py * Update save.py * Update save.py * patch saving * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * original_model * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * saving to RAM leakage? * Update save.py * new_save_directory * Update save.py * Update save.py * Update save.py * Update save.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml * Quick fixes * Update llama.py * Update llama.py * Update dpo.py * Update dpo.py * Update llama.py * Update save.py commitd691516ab9Author: Daniel Han <danielhanchen@gmail.com> Date: Fri Jan 19 04:51:19 2024 +1100 2024 Release (#96) * Fix tokenizer, dropout, bias for LoRA * Update loader.py * Fix LoRA downcasting * Update _utils.py * Saving to GGUF * fix * colab_quantize_to_gguf * move save modules * save module * Update __init__.py * Update save.py * Temp downgrade due to TRL issue * Fix up bugs * Faster saving + other changes * Update llama.py * Saving modules * spelling * Update llama.py * Update save.py * Update save.py * Update loader.py * Update llama.py * patch saving * Update save.py * Update save.py * Update save.py * patch saving * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * original_model * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * saving to RAM leakage? * Update save.py * new_save_directory * Update save.py * Update save.py * Update save.py * Update save.py * Update pyproject.toml * Update pyproject.toml * Update pyproject.toml commit9e2dec16fbAuthor: Daniel Han-Chen <danielhanchen@gmail.com> Date: Fri Jan 19 03:41:00 2024 +1100 Update pyproject.toml commit396c7245ddAuthor: Daniel Han-Chen <danielhanchen@gmail.com> Date: Fri Jan 19 03:35:17 2024 +1100 Update pyproject.toml commit738e91591fAuthor: Daniel Han <danielhanchen@gmail.com> Date: Thu Jan 11 04:08:03 2024 +1100 Fix some bugs (#83) * Fix tokenizer, dropout, bias for LoRA * Update loader.py * Fix LoRA downcasting * Update _utils.py * Saving to GGUF * fix * colab_quantize_to_gguf * move save modules * save module * Update __init__.py * Update save.py * Temp downgrade due to TRL issue * Fix up bugs commita1da50b5ceAuthor: Daniel Han <danielhanchen@gmail.com> Date: Wed Jan 10 23:10:48 2024 +1100 Update README.md (#81) commit606e8a9284Author: shimmy <107991372+shimmyshimmer@users.noreply.github.com> Date: Wed Jan 10 23:10:23 2024 +1100 Discord button redo (#80) commit0169294ffbAuthor: shimmy <107991372+shimmyshimmer@users.noreply.github.com> Date: Wed Jan 10 23:02:20 2024 +1100 Update logos (#79) * HF Perf Button * Update README.md Adding new buttons cleanup * Update README.md * Delete images/Discord.png * Delete images/try live demo green.png * new transparent logos * Revamping page * Revamp mainpage * Update README.md * Update README.md commitb2a8c33430Author: Daniel Han <danielhanchen@gmail.com> Date: Wed Jan 10 20:03:01 2024 +1100 Create FUNDING.yml (#78) commitc9c1abf290Author: Daniel Han-Chen <danielhanchen@gmail.com> Date: Wed Jan 10 01:02:44 2024 +1100 fix_tokenizer commit6efffb46e4Author: Daniel Han-Chen <danielhanchen@gmail.com> Date: Tue Jan 9 23:40:43 2024 +1100 check_tokenizer --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com>
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<a href="https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing"><img src="./images/Free version button.png" height="50"></a>
|
||||
<a href="https://discord.gg/u54VK8m8tk"><img src="./images/Discord button.png" height="50"></a>
|
||||
<a href="https://ko-fi.com/unsloth"><img src="./images/Kofi button.png" height="50"></a>
|
||||
</p>
|
||||
<div align="center">
|
||||
|
||||
<h2 align="center">
|
||||
Finetune Mistral, Llama 2-5x faster with 50% less memory!
|
||||
</h2>
|
||||
<br>
|
||||
<a href="https://unsloth.ai"><picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20logo%20white%20text.png">
|
||||
<source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20logo%20black%20text.png">
|
||||
<img alt="unsloth logo" src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20logo%20black%20text.png" height="110" style="max-width: 100%;">
|
||||
</picture></a>
|
||||
|
||||
<a href="https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing"><img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/start free finetune button.png" height="48"></a>
|
||||
<a href="https://discord.gg/u54VK8m8tk"><img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord button.png" height="48"></a>
|
||||
<a href="https://ko-fi.com/unsloth"><img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy me a coffee button.png" height="48"></a>
|
||||
|
||||
| Llama 2 7b | Mistral 7b | CodeLlama 34b | Llama 7b Kaggle 2x T4 |
|
||||
|-----------------------------|-----------------------------|-------------------------|------------------------|
|
||||
| **2.2x faster 43% less VRAM** | **2.2x faster 62% less VRAM** | **1.9x faster 27% less VRAM** | **5.5x faster 44% less VRAM** |
|
||||
| [⭐Llama **free** Colab notebook](https://colab.research.google.com/drive/1lBzz5KeZJKXjvivbYvmGarix9Ao6Wxe5?usp=sharing") | [⭐Mistral **free** Colab notebook](https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing) | [CodeLlama A100 Colab notebook](https://colab.research.google.com/drive/1y7A0AxE3y8gdj4AVkl2aZX47Xu3P1wJT?usp=sharing) | [⭐Kaggle **free** Alpaca notebook](https://www.kaggle.com/danielhanchen/unsloth-alpaca-t4-ddp)
|
||||
| [Llama A100 Colab notebook](https://colab.research.google.com/drive/1YIPY_18xm-K0iJDgvNkRoJsgkPMPAO3G?usp=sharing) | [Mistral A100 Colab notebook](https://colab.research.google.com/drive/1SKrKGV-BZoU4kv5q3g0jtE_OhRgPtrrQ?usp=sharing) | 50+ more examples below! | [⭐Kaggle **free** Slim Orca notebook](https://www.kaggle.com/danielhanchen/unsloth-slimorca-t4-ddp) |
|
||||
### Finetune Mistral, Llama 2-5x faster with 70% less memory!
|
||||
|
||||
* **NEW!** [DPO](https://arxiv.org/abs/2305.18290) support. ⭐**Free!** DPO Zephyr, Mistral example! <a href="https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing"><img src="./images/Colab.png" height="20"> [More info](#DPO) on DPO
|
||||
* **NEW!** [TinyLlama 1.1b](https://github.com/jzhang38/TinyLlama) on 3T tokens! ⭐**Free!** example <a href="https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?usp=sharing"><img src="./images/Colab.png" height="20">
|
||||
* **NEW!** We're in 🤗 Huggingface's official docs! We're on the [SFT docs](https://huggingface.co/docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth) and the [DPO docs](https://huggingface.co/docs/trl/main/en/dpo_trainer#accelerate-dpo-fine-tuning-using-unsloth)!
|
||||
* Supports Llama, Yi, Mistral, CodeLlama, Qwen (llamafied), Deepseek and their derived models (Open Hermes etc).
|
||||
* All kernels written in [OpenAI's Triton](https://openai.com/research/triton) language. **Manual backprop engine**.
|
||||
* **0% loss in accuracy** - no approximation methods - all exact.
|
||||
* No change of hardware. Supports NVIDIA GPUs since 2018+. Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20, 30, 40x, A100, H100, L40 etc) [Check your GPU!](https://developer.nvidia.com/cuda-gpus) GTX 1070, 1080 works, but is slow.
|
||||
* Works on **Linux** and **Windows** via WSL.
|
||||
* **NEW!** Download 4 bit models 4x faster from 🤗 Huggingface! Eg: `unsloth/mistral-7b-bnb-4bit`
|
||||
* Supports 4bit and 16bit QLoRA / LoRA finetuning via [bitsandbytes](https://github.com/TimDettmers/bitsandbytes).
|
||||
* **NEW!** Want a UI for finetuning? Try [Llama-Factory](https://github.com/hiyouga/LLaMA-Factory) and use `--use_unsloth`!
|
||||
* Open source trains 5x faster - see [Unsloth Pro](https://unsloth.ai/) for **30x faster training**!
|
||||
|
||||
|
||||
| 1 A100 40GB | 🤗 Hugging Face | Flash Attention | 🦥 Unsloth Open Source | [🦥 Unsloth Pro](https://unsloth.ai/pricing) |
|
||||
</div>
|
||||
|
||||
## ✨ Finetune for Free
|
||||
|
||||
All notebooks are **beginner friendly**! Colab provides a free GPU. Kaggle provides 30 hours for free per week.
|
||||
| Unsloth supports | Free Notebooks | Performance | Memory use |
|
||||
|-----------------|--------------------------------------------------------------------------------------------------------------------------|-------------|----------|
|
||||
| **Mistral 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing) | 2.2x faster | 62% less |
|
||||
| **Llama-2 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1lBzz5KeZJKXjvivbYvmGarix9Ao6Wxe5?usp=sharing) | 2.2x faster | 43% less |
|
||||
| **DPO - Zephyr** | [▶️ Start on Colab](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) | 1.9x faster | 19% less |
|
||||
| **TinyLlama** | [▶️ Start on Colab](https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?usp=sharing) | 3.9x faster | 74% less |
|
||||
| **CodeLlama 34b** A100 | [▶️ Start on Colab](https://colab.research.google.com/drive/1y7A0AxE3y8gdj4AVkl2aZX47Xu3P1wJT?usp=sharing) | 1.9x faster | 27% less |
|
||||
| **Mistral 7b** 2xT4 | [▶️ Start on Kaggle](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook) | 5x faster | 60% less |
|
||||
|
||||
- This [conversational notebook](https://colab.research.google.com/drive/1ef-tab5bhkvWmBOObepl1WgJvfvSzn5Q?usp=sharing) is useful for ShareGPT ChatML datatsets.
|
||||
- Our [raw text notebook](https://colab.research.google.com/drive/1bMOKOBzxQWUIGZBs_B0zm8pimuEnZdfM?usp=sharing) is useful for text completion.
|
||||
|
||||
## 🦥 Unsloth.ai News
|
||||
- 📣 [DPO support](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) is now included. [More info](#DPO) on DPO.
|
||||
- 📣 [TinyLlama 1.1b](https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?usp=sharing) on 3T tokens now works.
|
||||
- 📣 We did a [blog](https://huggingface.co/blog/unsloth-trl) with 🤗Hugging Face! We're in 🤗Hugging Face's official docs! Check out the [SFT docs](https://huggingface.co/docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth) and [DPO docs](https://huggingface.co/docs/trl/main/en/dpo_trainer#accelerate-dpo-fine-tuning-using-unsloth).
|
||||
- 📣 Now supports **Llama, Yi, Mistral, CodeLlama, Qwen (llamafied), Deepseek** and their derived models (**Open Hermes** etc). Llama 7, 13, 70b; CodeLlama 7, 13, 34, 70b; Yi 6, 34b are all supported!
|
||||
- 📣 **Download models 4x faster** from 🤗Hugging Face! Eg: `unsloth/mistral-7b-bnb-4bit` See our [HF collection](https://huggingface.co/collections/unsloth/load-4bit-models-4x-faster-659042e3a41c3cbad582e734) for more!
|
||||
|
||||
## 🔗 Links and Resources
|
||||
| Type | Links |
|
||||
| ------------------------------- | --------------------------------------- |
|
||||
| 📜 **Documentation** | [Read The Doc](https://github.com/unslothai/unsloth/tree/main#-documentation) |
|
||||
| 💾 **Installation** | [unsloth/README.md](https://github.com/unslothai/unsloth/tree/main#installation-instructions)|
|
||||
| <img height="14" src="https://upload.wikimedia.org/wikipedia/commons/6/6f/Logo_of_Twitter.svg" /> **Twitter (aka X)** | [Follow us on X](https://twitter.com/unslothai)|
|
||||
| 🥇 **Benchmarking** | [Performance Tables](https://github.com/unslothai/unsloth/tree/main#-performance-benchmarking)
|
||||
| 🌐 **Released Models** | [Unsloth Releases](https://huggingface.co/unsloth)|
|
||||
| ✍️ **Blog** | [Read our Blogs](https://unsloth.ai/blog)|
|
||||
|
||||
## ⭐ Key Features
|
||||
- All kernels written in [OpenAI's Triton](https://openai.com/research/triton) language. **Manual backprop engine**.
|
||||
- **0% loss in accuracy** - no approximation methods - all exact.
|
||||
- No change of hardware. Supports NVIDIA GPUs since 2018+. Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20, 30, 40x, A100, H100, L40 etc) [Check your GPU!](https://developer.nvidia.com/cuda-gpus) GTX 1070, 1080 works, but is slow.
|
||||
- Works on **Linux** and **Windows** via WSL.
|
||||
- Supports 4bit and 16bit QLoRA / LoRA finetuning via [bitsandbytes](https://github.com/TimDettmers/bitsandbytes).
|
||||
- Open source trains 5x faster - see [Unsloth Pro](https://unsloth.ai/) for **30x faster training**!
|
||||
- If you trained a model with 🦥Unsloth, you can use this cool sticker! <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made with unsloth.png" height="50" align="center" />
|
||||
|
||||
|
||||
## 🥇 Performance Benchmarking
|
||||
- For the full list of **reproducable** benchmarking tables, [go to our website](https://unsloth.ai/blog/mistral-benchmark#Benchmark%20tables)
|
||||
|
||||
| 1 A100 40GB | 🤗Hugging Face | Flash Attention | 🦥Unsloth Open Source | 🦥[Unsloth Pro](https://unsloth.ai/pricing) |
|
||||
|--------------|--------------|-----------------|---------------------|-----------------|
|
||||
| Alpaca | 1x | 1.04x | 1.98x | **15.64x** |
|
||||
| LAION Chip2 | 1x | 0.92x | 1.61x | **20.73x** |
|
||||
| OASST | 1x | 1.19x | 2.17x | **14.83x** |
|
||||
| Slim Orca | 1x | 1.18x | 2.22x | **14.82x** |
|
||||
|
||||
Join our [Discord](https://discord.gg/nsS4V5Z6ge)!
|
||||
- Benchmarking table below was conducted by [🤗Hugging Face](https://huggingface.co/blog/unsloth-trl).
|
||||
|
||||
<img src="./images/unsloth made with love.png" width="200" />
|
||||
If you trained a model with 🦥 Unsloth, we made a cool sticker if you want to use it!
|
||||
| Free Colab T4 | Dataset | 🤗Hugging Face | Pytorch 2.1.1 | 🦥Unsloth | 🦥 VRAM reduction |
|
||||
| --- | --- | --- | --- | --- | --- |
|
||||
| Llama-2 7b | OASST | 1x | 1.19x | 1.95x | -43.3% |
|
||||
| Mistral 7b | Alpaca | 1x | 1.07x | 1.56x | -13.7% |
|
||||
| Tiny Llama 1.1b | Alpaca | 1x | 2.06x | 3.87x | -73.8% |
|
||||
| DPO with Zephyr | Ultra Chat | 1x | 1.09x | 1.55x | -18.6% |
|
||||
|
||||
# Installation Instructions - Conda
|
||||
Select either `pytorch-cuda=11.8` for CUDA 11.8 or `pytorch-cuda=12.1` for CUDA 12.1.
|
||||
|
||||
|
||||
## 💾 Installation Instructions
|
||||
### Conda Installation
|
||||
Select either `pytorch-cuda=11.8` for CUDA 11.8 or `pytorch-cuda=12.1` for CUDA 12.1. If you have `mamba`, use `mamba` instead of `conda` for faster solving. See this [Github issue](https://github.com/unslothai/unsloth/issues/73) for help on debugging Conda installs.
|
||||
```bash
|
||||
conda install cudatoolkit xformers bitsandbytes pytorch pytorch-cuda=12.1 \
|
||||
-c pytorch -c nvidia -c xformers -c conda-forge -y
|
||||
conda install pytorch torchvision torchaudio pytorch-cuda=<12.1/11.8> -c pytorch -c nvidia
|
||||
|
||||
conda install xformers -c xformers -y
|
||||
|
||||
pip install bitsandbytes
|
||||
|
||||
pip install "unsloth[conda] @ git+https://github.com/unslothai/unsloth.git"
|
||||
```
|
||||
|
||||
# Installation Instructions - Pip
|
||||
### Pip Installation
|
||||
Do **NOT** use this if you have Anaconda. You must use the Conda install method, or else stuff will BREAK.
|
||||
|
||||
1. Find your CUDA version via
|
||||
```python
|
||||
import torch; torch.version.cuda
|
||||
```
|
||||
2. For Pytorch 2.1.0: You can update Pytorch via Pip (interchange `cu121` / `cu118`). Go to https://pytorch.org/ to learn more. Select either `cu118` for CUDA 11.8 or `cu121` for CUDA 12.1. If you have a RTX 3060 or higher (A100, H100 etc), use the `"ampere"` path. For Pytorch 2.1.1: got to step 3.
|
||||
2. For Pytorch 2.1.0: You can update Pytorch via Pip (interchange `cu121` / `cu118`). Go to https://pytorch.org/ to learn more. Select either `cu118` for CUDA 11.8 or `cu121` for CUDA 12.1. If you have a RTX 3060 or higher (A100, H100 etc), use the `"ampere"` path. For Pytorch 2.1.1: go to step 3. For Pytorch 2.2.0: go to step 4.
|
||||
```bash
|
||||
pip install --upgrade --force-reinstall --no-cache-dir torch==2.1.0 triton \
|
||||
--index-url https://download.pytorch.org/whl/cu121
|
||||
|
|
@ -84,16 +121,25 @@ pip install "unsloth[cu121_torch211] @ git+https://github.com/unslothai/unsloth.
|
|||
pip install "unsloth[cu118_ampere_torch211] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121_ampere_torch211] @ git+https://github.com/unslothai/unsloth.git"
|
||||
```
|
||||
4. We're working on Pytorch 2.1.2 support.
|
||||
4. For Pytorch 2.2.0: Use the `"ampere"` path for newer RTX 30xx GPUs or higher.
|
||||
```bash
|
||||
pip install --upgrade --force-reinstall --no-cache-dir torch==2.2.0 triton \
|
||||
--index-url https://download.pytorch.org/whl/cu121
|
||||
```
|
||||
```bash
|
||||
pip install "unsloth[cu118_torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121_torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu118_ampere_torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121_ampere_torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
```
|
||||
5. If you get errors, try the below first, then go back to step 1:
|
||||
```bash
|
||||
pip install --upgrade pip
|
||||
```
|
||||
|
||||
# Documentation
|
||||
We support Huggingface's TRL, Trainer, Seq2SeqTrainer or even Pytorch code!
|
||||
|
||||
We're in 🤗 Huggingface's official docs! We're on the [SFT docs](https://huggingface.co/docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth) and the [DPO docs](https://huggingface.co/docs/trl/main/en/dpo_trainer#accelerate-dpo-fine-tuning-using-unsloth)!
|
||||
## 📜 Documentation
|
||||
- We support Huggingface's TRL, Trainer, Seq2SeqTrainer or even Pytorch code!
|
||||
- We're in 🤗Hugging Face's official docs! Check out the [SFT docs](https://huggingface.co/docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth) and [DPO docs](https://huggingface.co/docs/trl/main/en/dpo_trainer#accelerate-dpo-fine-tuning-using-unsloth)!
|
||||
|
||||
```python
|
||||
from unsloth import FastLanguageModel
|
||||
|
|
@ -159,10 +205,10 @@ trainer.train()
|
|||
```
|
||||
|
||||
<a name="DPO"></a>
|
||||
# DPO (Direct Preference Optimization) Support
|
||||
DPO, PPO, Reward Modelling all seem to work as per 3rd party independent testing from [Llama-Factory](https://github.com/hiyouga/LLaMA-Factory). We have a preliminary Google Colab notebook for reproducing Zephyr on Tesla T4 here: [notebook](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing).
|
||||
## DPO Support
|
||||
DPO (Direct Preference Optimization), PPO, Reward Modelling all seem to work as per 3rd party independent testing from [Llama-Factory](https://github.com/hiyouga/LLaMA-Factory). We have a preliminary Google Colab notebook for reproducing Zephyr on Tesla T4 here: [notebook](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing).
|
||||
|
||||
We're in 🤗 Huggingface's official docs! We're on the [SFT docs](https://huggingface.co/docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth) and the [DPO docs](https://huggingface.co/docs/trl/main/en/dpo_trainer#accelerate-dpo-fine-tuning-using-unsloth)!
|
||||
We're in 🤗Hugging Face's official docs! We're on the [SFT docs](https://huggingface.co/docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth) and the [DPO docs](https://huggingface.co/docs/trl/main/en/dpo_trainer#accelerate-dpo-fine-tuning-using-unsloth)!
|
||||
|
||||
```python
|
||||
from unsloth import FastLanguageModel, PatchDPOTrainer
|
||||
|
|
@ -217,17 +263,76 @@ dpo_trainer = DPOTrainer(
|
|||
dpo_trainer.train()
|
||||
```
|
||||
|
||||
# Support us!
|
||||
We're currently 2 brothers trying to make LLMs for everyone! It'll be super cool if you can support our work!!
|
||||
<a href="https://ko-fi.com/unsloth"><img src="./images/Kofi button.png" height="50"></a>
|
||||
## 🥇 Detailed Benchmarking Tables
|
||||
- Click "Code" for fully reproducible examples
|
||||
- "Unsloth Equal" is a preview of our PRO version, with code stripped out. All settings and the loss curve remains identical.
|
||||
- For the full list of benchmarking tables, [go to our website](https://unsloth.ai/blog/mistral-benchmark#Benchmark%20tables)
|
||||
|
||||
| 1 A100 40GB | 🤗Hugging Face | Flash Attention 2 | 🦥Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Alpaca | 1x | 1.04x | 1.98x | 2.48x | 5.32x | **15.64x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/1u4dBeM-0vGNVmmO6X7cScAut-Hyt4KDF?usp=sharing) | [Code](https://colab.research.google.com/drive/1fgTOxpMbVjloQBvZyz4lF4BacKSZOB2A?usp=sharing) | [Code](https://colab.research.google.com/drive/1YIPY_18xm-K0iJDgvNkRoJsgkPMPAO3G?usp=sharing) | [Code](https://colab.research.google.com/drive/1ANW8EFL3LVyTD7Gq4TkheC1Z7Rxw-rHp?usp=sharing) | | |
|
||||
| seconds| 1040 | 1001 | 525 | 419 | 196 | 67 |
|
||||
| memory MB| 18235 | 15365 | 9631 | 8525 | | |
|
||||
| % saved| | 15.74 | 47.18 | 53.25 | | | |
|
||||
|
||||
# Future Milestones and limitations
|
||||
1. Support Mixtral.
|
||||
2. Supports all Mistral, Llama type models, but some are unoptimized (Qwen with biases)
|
||||
3. Dropout, bias in LoRA matrices are supported, just not optimized.
|
||||
### Llama-Factory 3rd party benchmarking
|
||||
- [Link to performance table.](https://github.com/hiyouga/LLaMA-Factory/wiki/Performance-Comparison) TGS: tokens per GPU per second. Model: LLaMA2-7B. GPU: NVIDIA A100 * 1. Batch size: 4. Gradient accumulation: 2. LoRA rank: 8. Max length: 1024.
|
||||
|
||||
# Performance comparisons on 1 Tesla T4 GPU:
|
||||
**Time taken for 1 epoch**
|
||||
| Method | Bits | TGS | GRAM | Speed |
|
||||
| --- | --- | --- | --- | --- |
|
||||
| HF | 16 | 2392 | 18GB | 100% |
|
||||
| HF+FA2 | 16 | 2954 | 17GB | 123% |
|
||||
| Unsloth+FA2 | 16 | 4007 | 16GB | **168%** |
|
||||
| HF | 4 | 2415 | 9GB | 101% |
|
||||
| Unsloth+FA2 | 4 | 3726 | 7GB | **160%** |
|
||||
|
||||
### Performance comparisons between popular models
|
||||
<details>
|
||||
<summary>Click for specific model benchmarking tables (Mistral 7b, CodeLlama 34b etc.)</summary>
|
||||
|
||||
### Mistral 7b
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Mistral 7B Slim Orca | 1x | 1.15x | 2.15x | 2.53x | 4.61x | **13.69x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/1mePk3KzwTD81hr5mcNcs_AX3Kbg_Ha0x?usp=sharing) | [Code](https://colab.research.google.com/drive/1dgHxjvTmX6hb0bPcLp26RXSE6_n9DKj7?usp=sharing) | [Code](https://colab.research.google.com/drive/1SKrKGV-BZoU4kv5q3g0jtE_OhRgPtrrQ?usp=sharing) | [Code](https://colab.research.google.com/drive/18yOiyX0T81mTwZqOALFSCX_tSAqju6aD?usp=sharing) | |
|
||||
| seconds | 1813 | 1571 | 842 | 718 | 393 | 132 |
|
||||
| memory MB | 32853 | 19385 | 12465 | 10271 | | |
|
||||
| % saved| | 40.99 | 62.06 | 68.74 | | |
|
||||
|
||||
### CodeLlama 34b
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Code Llama 34B | OOM ❌ | 0.99x | 1.87x | 2.61x | 4.27x | 12.82x |
|
||||
| code | [▶️ Code](https://colab.research.google.com/drive/1ykfz3BqrtC_AUFegCzUQjjfUNlxp6Otc?usp=sharing) | [Code](https://colab.research.google.com/drive/12ZypxQh7OC6kBXvWZI-5d05I4m-B_hoR?usp=sharing) | [Code](https://colab.research.google.com/drive/1gdHyAx8XJsz2yNV-DHvbHjR1iCef5Qmh?usp=sharing) | [Code](https://colab.research.google.com/drive/1fm7wqx9MJ0kRrwKOfmLkK1Rmw-pySahB?usp=sharing) | |
|
||||
| seconds | 1953 | 1982 | 1043 | 748 | 458 | 152 |
|
||||
| memory MB | 40000 | 33217 | 27413 | 22161 | | |
|
||||
| % saved| | 16.96| 31.47 | 44.60 | | | |
|
||||
|
||||
### 1 Tesla T4
|
||||
|
||||
| 1 T4 16GB | Hugging Face | Flash Attention | Unsloth Open | Unsloth Pro Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-----------------|-----------------|---------------|---------------|-------------|
|
||||
| Alpaca | 1x | 1.09x | 1.69x | 1.79x | 2.93x | **8.3x** |
|
||||
| code | [▶️ Code](https://colab.research.google.com/drive/1XpLIV4s8Bj5uryB-X2gqM88oRGHEGdaB?usp=sharing) | [Code](https://colab.research.google.com/drive/1LyXu6CjuymQg6ddHX8g1dpUvrMa1nn4L?usp=sharing) | [Code](https://colab.research.google.com/drive/1gsv4LpY7C32otl1rgRo5wXTk4HIitXoM?usp=sharing) | [Code](https://colab.research.google.com/drive/1VtULwRQwhEnVdNryjm27zXfdSM1tNfFK?usp=sharing) | | |
|
||||
| seconds | 1599 | 1468 | 942 | 894 | 545 | 193 |
|
||||
| memory MB | 7199 | 7059 | 6459 | 5443 | | |
|
||||
| % saved | | 1.94 | 10.28 | 24.39 | | |
|
||||
|
||||
### 2 Tesla T4s via DDP
|
||||
|
||||
| 2 T4 DDP | Hugging Face | Flash Attention | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|----------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Alpaca | 1x | 0.99x | 4.95x | 4.44x | 7.28x | **20.61x** |
|
||||
| code | [▶️ Code](https://www.kaggle.com/danielhanchen/hf-original-alpaca-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/hf-sdpa-alpaca-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/unsloth-alpaca-t4-ddp) | | |
|
||||
| seconds | 9882 | 9946 | 1996 | 2227 | 1357 | 480 |
|
||||
| memory MB| 9176 | 9128 | 6904 | 6782 | | |
|
||||
| % saved | | 0.52 | 24.76 | 26.09 | | | |
|
||||
</details>
|
||||
|
||||
### Performance comparisons on 1 Tesla T4 GPU:
|
||||
<details>
|
||||
<summary>Click for Time taken for 1 epoch</summary>
|
||||
|
||||
One Tesla T4 on Google Colab
|
||||
`bsz = 2, ga = 4, max_grad_norm = 0.3, num_train_epochs = 1, seed = 3047, lr = 2e-4, wd = 0.01, optim = "adamw_8bit", schedule = "linear", schedule_steps = 10`
|
||||
|
|
@ -247,8 +352,10 @@ One Tesla T4 on Google Colab
|
|||
| Unsloth Open | 1 T4 | 6.8GB | 5.7GB | 7.8GB | 7.7GB |
|
||||
| Unsloth Pro | 1 T4 | 6.4GB | 6.4GB | 6.4GB | 6.4GB |
|
||||
| Unsloth Max | 1 T4 | 11.4GB | 12.4GB | 11.9GB | 14.4GB |
|
||||
</details>
|
||||
|
||||
# Performance comparisons on 2 Tesla T4 GPUs via DDP:
|
||||
<details>
|
||||
<summary>Click for Performance Comparisons on 2 Tesla T4 GPUs via DDP:</summary>
|
||||
**Time taken for 1 epoch**
|
||||
|
||||
Two Tesla T4s on Kaggle
|
||||
|
|
@ -269,173 +376,12 @@ Two Tesla T4s on Kaggle
|
|||
| Unsloth Max | 2 T4 | 10.5GB \| 5GB | 10.6GB \| 5GB | 10.6GB \| 5GB | 10.5GB \| 5GB * |
|
||||
|
||||
* Slim Orca `bsz=1` for all benchmarks since `bsz=2` OOMs. We can handle `bsz=2`, but we benchmark it with `bsz=1` for consistency.
|
||||
</details>
|
||||
|
||||
# Llama-Factory 3rd party benchmarking
|
||||
|
||||
<br>
|
||||
|
||||
| Method | Bits | TGS | GRAM | Speed |
|
||||
| --- | --- | --- | --- | --- |
|
||||
| HF | 16 | 2392 | 18GB | 100% |
|
||||
| HF+FA2 | 16 | 2954 | 17GB | 123% |
|
||||
| Unsloth+FA2 | 16 | 4007 | 16GB | **168%** |
|
||||
| HF | 4 | 2415 | 9GB | 101% |
|
||||
| Unsloth+FA2 | 4 | 3726 | 7GB | **160%** |
|
||||
|
||||
[Link](https://github.com/hiyouga/LLaMA-Factory/wiki/Performance-Comparison) to performance table. TGS: tokens per GPU per second. Model: LLaMA2-7B. GPU: NVIDIA A100 * 1. Batch size: 4. Gradient accumulation: 2. LoRA rank: 8. Max length: 1024.
|
||||
|
||||
# How did we make it faster?
|
||||
Manual autograd, Triton kernels etc. See our [Benchmark Breakdown](https://unsloth.ai/blog/mistral-benchmark) for more info!
|
||||
|
||||
# Troubleshooting
|
||||
1. Sometimes `bitsandbytes` or `xformers` does not link properly. Try running:
|
||||
```bash
|
||||
!ldconfig /usr/lib64-nvidia
|
||||
```
|
||||
2. Windows is not supported as of yet - we rely on Xformers and Triton support, so until both packages support Windows officially, Unsloth will then support Windows.
|
||||
|
||||
3. If it doesn't install - maybe try updating `pip`.
|
||||
|
||||
|
||||
# Full benchmarking tables
|
||||
Click "Code" for a fully reproducible example.
|
||||
"Unsloth Equal" is a preview of our PRO version, with code stripped out. All settings and the loss curve remains identical.
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Alpaca | 1x | 1.04x | 1.98x | 2.48x | 5.32x | **15.64x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/1u4dBeM-0vGNVmmO6X7cScAut-Hyt4KDF?usp=sharing) | [Code](https://colab.research.google.com/drive/1fgTOxpMbVjloQBvZyz4lF4BacKSZOB2A?usp=sharing) | [Code](https://colab.research.google.com/drive/1YIPY_18xm-K0iJDgvNkRoJsgkPMPAO3G?usp=sharing) | [Code](https://colab.research.google.com/drive/1ANW8EFL3LVyTD7Gq4TkheC1Z7Rxw-rHp?usp=sharing) | | |
|
||||
| seconds| 1040 | 1001 | 525 | 419 | 196 | 67 |
|
||||
| memory MB| 18235 | 15365 | 9631 | 8525 | | |
|
||||
| % saved| | 15.74 | 47.18 | 53.25 | | | |
|
||||
|
||||
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| LAION Chip2 | 1x | 0.92x | 1.61x | 1.84x | 7.05x | **20.73x** |
|
||||
| code |[Code](https://colab.research.google.com/drive/1gjL1TaKwc_xv2TcxJC8QWEWBG1msh3g2?usp=sharing) | [Code](https://colab.research.google.com/drive/15vlPjMr8xDj5BFhGdqunGaOQSMqXPEXU?usp=sharing) | [Code](https://colab.research.google.com/drive/1zPwvf-BmHyHlPMBxDsY8zS0BnQ-KKbCc?usp=sharing) | [Code](https://colab.research.google.com/drive/1X2uHy-arRsZxqWHvKHwwW102JaMwChD2?usp=sharing) | | |
|
||||
| seconds| 581 | 631 | 361 | 315 | 82 | 28 |
|
||||
| memory MB| 7763 | 8047 | 7763 | 6441 | | |
|
||||
| % saved| | -3.66 | 0.00 | 17.03 | | | |
|
||||
|
||||
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| OASST | 1x | 1.19x | 2.17x | 2.66x | 5.04x | **14.83x** |
|
||||
| code |[Code](https://colab.research.google.com/drive/10NzDreFbuWELGUuBv0MOoC7y3MBewaNx?usp=sharing) | [Code](https://colab.research.google.com/drive/1TwdkJ1sHsuEH-kgeCPqSFeCpOnCfz6Ou?usp=sharing) | [Code](https://colab.research.google.com/drive/1AkwjUkOF0XeRBMT_S8Uhh74kitEsZHla?usp=sharing) | [Code](https://colab.research.google.com/drive/1roMkp2UjbeK2t3DkNz50cRs1MT92RPFT?usp=sharing) | | |
|
||||
| seconds| 1852 | 1558 | 852 | 696 | 367 | 125 |
|
||||
| memory MB| 26431 | 16565 | 12267| 11223| | |
|
||||
| % saved| | 37.33 | 53.59 | 57.54 | | |
|
||||
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Slim Orca | 1x | 1.18x | 2.22x | 2.64x | 5.04x | **14.82x** |
|
||||
| code |[Code](https://colab.research.google.com/drive/1UNo1xsMl8YH7xnWnIVjDFnCAPfc0RGgu?usp=sharing) | [Code](https://colab.research.google.com/drive/1zbphER-SKhbSWGjHTfnBLPFyTgIVvaeH?usp=sharing) | [Code](https://colab.research.google.com/drive/156si33585iv4Uh-VILFglUmIMrNCNuc2?usp=sharing) | [Code](https://colab.research.google.com/drive/1_mhZy7dfl9jEnJRuJBZJ5y3OwW06jgQA?usp=sharing) | | |
|
||||
| seconds| 1824 | 1545 | 821 | 691 | 362 | 123 |
|
||||
| memory MB| 24557 | 15681 | 10595| 9007 | | |
|
||||
| % saved| | 36.14 | 56.86 | 63.32 | | |
|
||||
|
||||
### Mistral 7b
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Mistral 7B Slim Orca | 1x | 1.15x | 2.15x | 2.53x | 4.61x | **13.69x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/1mePk3KzwTD81hr5mcNcs_AX3Kbg_Ha0x?usp=sharing) | [Code](https://colab.research.google.com/drive/1dgHxjvTmX6hb0bPcLp26RXSE6_n9DKj7?usp=sharing) | [Code](https://colab.research.google.com/drive/1SKrKGV-BZoU4kv5q3g0jtE_OhRgPtrrQ?usp=sharing) | [Code](https://colab.research.google.com/drive/18yOiyX0T81mTwZqOALFSCX_tSAqju6aD?usp=sharing) | |
|
||||
| seconds | 1813 | 1571 | 842 | 718 | 393 | 132 |
|
||||
| memory MB | 32853 | 19385 | 12465 | 10271 | | |
|
||||
| % saved| | 40.99 | 62.06 | 68.74 | | |
|
||||
|
||||
### CodeLlama 34b
|
||||
| 1 A100 40GB | Hugging Face | Flash Attention 2 | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Code Llama 34B | OOM ❌ | 0.99x | 1.87x | 2.61x | 4.27x | 12.82x |
|
||||
| code | [Code](https://colab.research.google.com/drive/1ykfz3BqrtC_AUFegCzUQjjfUNlxp6Otc?usp=sharing) | [Code](https://colab.research.google.com/drive/12ZypxQh7OC6kBXvWZI-5d05I4m-B_hoR?usp=sharing) | [Code](https://colab.research.google.com/drive/1gdHyAx8XJsz2yNV-DHvbHjR1iCef5Qmh?usp=sharing) | [Code](https://colab.research.google.com/drive/1fm7wqx9MJ0kRrwKOfmLkK1Rmw-pySahB?usp=sharing) | |
|
||||
| seconds | 1953 | 1982 | 1043 | 748 | 458 | 152 |
|
||||
| memory MB | 40000 | 33217 | 27413 | 22161 | | |
|
||||
| % saved| | 16.96| 31.47 | 44.60 | | | |
|
||||
|
||||
### 1 Tesla T4
|
||||
|
||||
| 1 T4 16GB | Hugging Face | Flash Attention | Unsloth Open | Unsloth Pro Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-----------------|-----------------|---------------|---------------|-------------|
|
||||
| Alpaca | 1x | 1.09x | 1.69x | 1.79x | 2.93x | **8.3x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/1XpLIV4s8Bj5uryB-X2gqM88oRGHEGdaB?usp=sharing) | [Code](https://colab.research.google.com/drive/1LyXu6CjuymQg6ddHX8g1dpUvrMa1nn4L?usp=sharing) | [Code](https://colab.research.google.com/drive/1gsv4LpY7C32otl1rgRo5wXTk4HIitXoM?usp=sharing) | [Code](https://colab.research.google.com/drive/1VtULwRQwhEnVdNryjm27zXfdSM1tNfFK?usp=sharing) | | |
|
||||
| seconds | 1599 | 1468 | 942 | 894 | 545 | 193 |
|
||||
| memory MB | 7199 | 7059 | 6459 | 5443 | | |
|
||||
| % saved | | 1.94 | 10.28 | 24.39 | | |
|
||||
|
||||
| 1 T4 16GB | Hugging Face | Flash Attention | Unsloth Open | Unsloth Pro Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-----------------|-----------------|---------------|---------------|-------------|
|
||||
| LAION Chip2 | 1x | 0.99x | 1.80x | 1.75x | 4.15x | **11.75x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/1EtdStADehE4FVJnU2Cu6O8p9jDYdqG2L?usp=sharing) | [Code](https://colab.research.google.com/drive/1Ik4jO68odUiQIJ_szZ3xok5fk58WpA5Q?usp=sharing) | [Code](https://colab.research.google.com/drive/1E2nR4V3bXIWBQIUE7uR39lYPr3UikzqH?usp=sharing) | [Code](https://colab.research.google.com/drive/13jbj8D8FOt9KyXwZt9Yf2MsYkD8CyCVR?usp=sharing) | | |
|
||||
| seconds | 952 | 955 | 529 | 543 | 229 | 81 |
|
||||
| memory MB | 6037 | 6033 | 5797 | 4855 | | |
|
||||
| % saved | | 0.07 | 3.98 | 19.58 | | |
|
||||
|
||||
| 1 T4 16GB | Hugging Face | Flash Attention | Unsloth Open | Unsloth Pro Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-----------------|-----------------|---------------|---------------|-------------|
|
||||
| OASST | 1x | 1.19x | 1.95x | 1.86x | 2.58x | **7.3x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/1aXzGgEM3yYB6SWy_XR81nQFWME40ksSy?usp=sharing) | [Code](https://colab.research.google.com/drive/1-5MdIOp0cM0scC-CdRZhh8OYhnGHqct4?usp=sharing) | [Code](https://colab.research.google.com/drive/1n-fgduZhRUsSjgpqNtVkXA3rSfE7iBdg?usp=sharing) | [Code](https://colab.research.google.com/drive/1z_GlHr2M_bB4lQrPhdWC7dseZv23cBIy?usp=sharing) | | |
|
||||
| seconds | 2640 | 2222 | 1355 | 1421 | 1024 | 362 |
|
||||
| memory MB | 14827 | 10391 | 8413 | 7031 | | |
|
||||
| % saved | | 29.92 | 43.26 | 52.58 | | |
|
||||
|
||||
| 1 T4 16GB | Hugging Face | Flash Attention | Unsloth Open | Unsloth Pro Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|-------------|-----------------|-----------------|---------------|---------------|-------------|
|
||||
| Slim Orca | 1x | 1.21x | 1.77x | 1.85x | 2.71x | **7.67x** |
|
||||
| code | [Code](https://colab.research.google.com/drive/15yLlJx9IE84kzx7ikky45pRcarPyUtEs?usp=sharing) | [Code](https://colab.research.google.com/drive/16IShIBmjKULWy87I-xURpj4nztTkAF13?usp=sharing) | [Code](https://colab.research.google.com/drive/1CJG3XLg_OQpCz71eB7Uqx7wuK_n2b-a8?usp=sharing) | [Code](https://colab.research.google.com/drive/1UmwuWHtlrC6MAfl9mX7A_TRfo5iSHDa-?usp=sharing) | | |
|
||||
| seconds | 2735 | 2262 | 1545 | 1478 | 1009 | 356 |
|
||||
| memory MB | 13933 | 10489 | 7661 | 6563 | | |
|
||||
| % saved | | 24.72 | 45.02 | 52.90 | | |
|
||||
|
||||
### 2 Tesla T4s via DDP
|
||||
|
||||
| 2 T4 DDP | Hugging Face | Flash Attention | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|----------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Alpaca | 1x | 0.99x | 4.95x | 4.44x | 7.28x | **20.61x** |
|
||||
| code | [Code](https://www.kaggle.com/danielhanchen/hf-original-alpaca-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/hf-sdpa-alpaca-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/unsloth-alpaca-t4-ddp) | | |
|
||||
| seconds | 9882 | 9946 | 1996 | 2227 | 1357 | 480 |
|
||||
| memory MB| 9176 | 9128 | 6904 | 6782 | | |
|
||||
| % saved | | 0.52 | 24.76 | 26.09 | | | |
|
||||
|
||||
| 2 T4 DDP | Hugging Face | Flash Attention | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|----------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| LAION Chip2 | 1x | 1.12x | 5.28x | 4.21x | 10.01x | **28.32x** |
|
||||
| code | [Code](https://www.kaggle.com/danielhanchen/hf-original-laion-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/hf-sdpa-laion-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/unsloth-laion-t4-ddp) | | |
|
||||
| seconds | 5418 | 4854 | 1027 | 1286 | 541 | 191 |
|
||||
| memory MB| 7316 | 7316 | 5732 | 5934 | | |
|
||||
| % saved | | 0.00 | 21.65 | 18.89 | | |
|
||||
|
||||
| 2 T4 DDP | Hugging Face | Flash Attention | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|----------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| OASST (bsz=1) | 1x | 1.14x | 5.56x | 5.09x | 5.64x | **15.97x** |
|
||||
| code | [Code](https://www.kaggle.com/danielhanchen/hf-original-oasst-bsz1-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/hf-sdpa-oasst-bsz1-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/unsloth-oasst-bsz1-t4-ddp) | | | |
|
||||
| seconds | 4503 | 3955 | 811 | 885 | 798 | 282 |
|
||||
| memory MB | 11896 | 11628 | 6616 | 7105 | | |
|
||||
| % saved | | 2.25 | 44.38 | 40.27 | | |
|
||||
|
||||
| 2 T4 DDP | Hugging Face | Flash Attention | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|----------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Slim Orca (bsz=1) | 1x | 0.97x | 5.54x | 4.68x | 6.88x | **19.46x** |
|
||||
| code | [Code](https://www.kaggle.com/danielhanchen/hf-original-slimorca-bsz1-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/hf-sdpa-slimorca-bsz1-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/unsloth-slimorca-bsz1-t4-ddp) | | |
|
||||
| seconds | 4042 | 4158 | 729 | 863 | 588 | 208 |
|
||||
| memory MB| 11010 | 11042 | 6492 | 7410 | | |
|
||||
| % saved | | -0.29| 41.04 | 32.70 | | | |
|
||||
|
||||
| 2 T4 DDP | Hugging Face | Flash Attention | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|----------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| OASST (bsz=2) | OOM ❌ | OOM ❌ | ✓ | ✓ | ✓ | ✓ |
|
||||
| code | [Code](https://www.kaggle.com/danielhanchen/hf-original-oasst-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/hf-sdpa-oasst-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/unsloth-oasst-t4-ddp) | | | |
|
||||
| seconds | OOM | OOM | 2719 | 3391 | 2794 | 987 |
|
||||
| memory MB| OOM | OOM | 8134 | 9600 | | |
|
||||
| % saved | OOM | OOM | | | | |
|
||||
|
||||
| 2 T4 DDP | Hugging Face | Flash Attention | Unsloth Open | Unsloth Equal | Unsloth Pro | Unsloth Max |
|
||||
|--------------|----------|-------------|-----------------|--------------|---------------|-------------|
|
||||
| Slim Orca (bsz=2) | OOM ❌ | OOM ❌ | ✓ | ✓ | ✓ |✓ |
|
||||
| code | [Code](https://www.kaggle.com/danielhanchen/hf-original-slimorca-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/hf-sdpa-slimorca-t4-ddp) | [Code](https://www.kaggle.com/danielhanchen/unsloth-slimorca-t4-ddp) | | |
|
||||
| seconds | OOM | OOM | 2990 | 3444 | 2351 | 831 |
|
||||
| memory MB| OOM | OOM | 7594 | 8881 | | |
|
||||
| % saved | OOM | OOM | | | | |
|
||||
|
||||
# Credits
|
||||
### Credits
|
||||
1. [RandomInternetPreson](https://github.com/RandomInternetPreson) for confirming WSL support
|
||||
2. [152334H](https://github.com/152334H) for experimental DPO support
|
||||
3. [atgctg](https://github.com/atgctg) for syntax highlighting
|
||||
<img src="./images/unsloth loading page render.png" width="300" />
|
||||
|
|
|
|||
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images/buy me a coffee button.png
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After Width: | Height: | Size: 18 KiB |
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images/made with unsloth.png
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images/made with unsloth.png
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After Width: | Height: | Size: 69 KiB |
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images/start free finetune button.png
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After Width: | Height: | Size: 11 KiB |
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images/unsloth end.png
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After Width: | Height: | Size: 871 KiB |
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Reference in a new issue