mirror of
https://github.com/amazon-science/chronos-forecasting
synced 2026-05-24 10:08:33 +00:00
Update Notebooks and README (#356)
*Issue #, if available:* *Description of changes:* By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice. --------- Co-authored-by: Oleksandr Shchur <oleks.shchur@gmail.com>
This commit is contained in:
parent
dc5c438ab2
commit
c5aa5f4292
2 changed files with 22 additions and 5 deletions
15
README.md
15
README.md
|
|
@ -56,6 +56,10 @@ To perform inference with Chronos, the easiest way is to install this package th
|
||||||
pip install chronos-forecasting
|
pip install chronos-forecasting
|
||||||
```
|
```
|
||||||
|
|
||||||
|
> [!TIP]
|
||||||
|
> For reliable production use, we recommend using Chronos-2 models through [Amazon SageMaker JumpStart](https://aws.amazon.com/sagemaker/ai/jumpstart/). Check out [this tutorial](notebooks/deploy-chronos-to-amazon-sagemaker.ipynb) to learn how to deploy Chronos-2 inference endpoints to AWS with just a few lines of code.
|
||||||
|
|
||||||
|
|
||||||
### Forecasting
|
### Forecasting
|
||||||
|
|
||||||
A minimal example showing how to perform forecasting using Chronos-2:
|
A minimal example showing how to perform forecasting using Chronos-2:
|
||||||
|
|
@ -111,8 +115,15 @@ plt.legend()
|
||||||
## Example Notebooks
|
## Example Notebooks
|
||||||
|
|
||||||
- [Chronos-2 Quick Start](notebooks/chronos-2-quickstart.ipynb)
|
- [Chronos-2 Quick Start](notebooks/chronos-2-quickstart.ipynb)
|
||||||
- [Deploy Chronos-Bolt on Amazon SageMaker](notebooks/deploy-chronos-bolt-to-amazon-sagemaker.ipynb)
|
|
||||||
- Deploy Chronos-2 on Amazon SageMaker (coming soon!)
|
<a href="https://studiolab.sagemaker.aws/import/github/amazon-science/chronos-forecasting/blob/main/notebooks/chronos-2-quickstart.ipynb">
|
||||||
|
<img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In SageMaker Studio Lab" height="18" align="absmiddle">
|
||||||
|
</a>
|
||||||
|
|
||||||
|
<a href="https://colab.research.google.com/github/amazon-science/chronos-forecasting/blob/main/notebooks/chronos-2-quickstart.ipynb">
|
||||||
|
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" height="18" align="absmiddle">
|
||||||
|
</a>
|
||||||
|
- [Deploy Chronos-2 on Amazon SageMaker](notebooks/deploy-chronos-to-amazon-sagemaker.ipynb)
|
||||||
|
|
||||||
## 📝 Citation
|
## 📝 Citation
|
||||||
|
|
||||||
|
|
|
||||||
|
|
@ -7,6 +7,12 @@
|
||||||
"source": [
|
"source": [
|
||||||
"# Getting Started with Chronos-2\n",
|
"# Getting Started with Chronos-2\n",
|
||||||
"\n",
|
"\n",
|
||||||
|
"[](https://studiolab.sagemaker.aws/import/github/amazon-science/chronos-forecasting/blob/main/notebooks/chronos-2-quickstart.ipynb)\n",
|
||||||
|
"[](\n",
|
||||||
|
"https://colab.research.google.com/github/amazon-science/chronos-forecasting/blob/main/notebooks/chronos-2-quickstart.ipynb)\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
"**Chronos-2** is a foundation model for time series forecasting that builds on [Chronos](https://arxiv.org/abs/2403.07815) and [Chronos-Bolt](https://aws.amazon.com/blogs/machine-learning/fast-and-accurate-zero-shot-forecasting-with-chronos-bolt-and-autogluon/). It offers significant improvements in capabilities and can handle diverse forecasting scenarios not supported by earlier models.\n",
|
"**Chronos-2** is a foundation model for time series forecasting that builds on [Chronos](https://arxiv.org/abs/2403.07815) and [Chronos-Bolt](https://aws.amazon.com/blogs/machine-learning/fast-and-accurate-zero-shot-forecasting-with-chronos-bolt-and-autogluon/). It offers significant improvements in capabilities and can handle diverse forecasting scenarios not supported by earlier models.\n",
|
||||||
"\n",
|
"\n",
|
||||||
"| Capability | Chronos | Chronos-Bolt | Chronos-2 |\n",
|
"| Capability | Chronos | Chronos-Bolt | Chronos-2 |\n",
|
||||||
|
|
@ -31,7 +37,7 @@
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
"%pip install -U 'chronos-forecasting>=2.0' 'pandas[pyarrow]' 'matplotlib'"
|
"%pip install 'chronos-forecasting>=2.0' 'pandas[pyarrow]' 'matplotlib'"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
|
|
@ -41,9 +47,9 @@
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
"# Use only 1 GPU if available\n",
|
|
||||||
"import os\n",
|
"import os\n",
|
||||||
"\n",
|
"\n",
|
||||||
|
"# Use only 1 GPU if available\n",
|
||||||
"os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
|
"os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
|
||||||
"\n",
|
"\n",
|
||||||
"import pandas as pd\n",
|
"import pandas as pd\n",
|
||||||
|
|
@ -1586,7 +1592,7 @@
|
||||||
"name": "python",
|
"name": "python",
|
||||||
"nbconvert_exporter": "python",
|
"nbconvert_exporter": "python",
|
||||||
"pygments_lexer": "ipython3",
|
"pygments_lexer": "ipython3",
|
||||||
"version": "3.11.11"
|
"version": "3.11.13"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
|
|
|
||||||
Loading…
Reference in a new issue