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Add optional inference params to example (#15)

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*Description of changes:* This PR adds optional inference params such as
`num_samples`, `top_k`, etc. to the example in the README for clarity.


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Abdul Fatir 2024-03-18 13:13:06 +01:00 committed by GitHub
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10
README.md
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@ -37,6 +37,7 @@ pip install git+https://github.com/amazon-science/chronos-forecasting.git
A minimal example showing how to perform inference using Chronos models:
```python
# for plotting, run: pip install pandas matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
@ -55,7 +56,14 @@ df = pd.read_csv("https://raw.githubusercontent.com/AileenNielsen/TimeSeriesAnal
# or a left-padded 2D tensor with batch as the first dimension
context = torch.tensor(df["#Passengers"])
prediction_length = 12
forecast = pipeline.predict(context, prediction_length) # shape [num_series, num_samples, prediction_length]
forecast = pipeline.predict(
context,
prediction_length,
num_samples=20,
temperature=1.0,
top_k=50,
top_p=1.0,
) # forecast shape: [num_series, num_samples, prediction_length]
# visualize the forecast
forecast_index = range(len(df), len(df) + prediction_length)