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oxfrug
/
chronos-2-int8-torchao

Time Series Forecasting
Chronos
Safetensors
t5
time-series
forecasting
chronos
chronos-2
quantization
torchao
int8
8-bit precision
Model card Files Files and versions
xet
Community

Instructions to use oxfrug/chronos-2-int8-torchao with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Chronos

    How to use oxfrug/chronos-2-int8-torchao with Chronos:

    pip install chronos-forecasting
    import pandas as pd
    from chronos import BaseChronosPipeline
    
    pipeline = BaseChronosPipeline.from_pretrained("oxfrug/chronos-2-int8-torchao", device_map="cuda")
    
    # Load historical data
    context_df = pd.read_csv("https://autogluon.s3.us-west-2.amazonaws.com/datasets/timeseries/misc/AirPassengers.csv")
    
    # Generate predictions
    pred_df = pipeline.predict_df(
        context_df,
        prediction_length=36,  # Number of steps to forecast
        quantile_levels=[0.1, 0.5, 0.9],  # Quantiles for probabilistic forecast
        id_column="item_id",  # Column identifying different time series
        timestamp_column="Month",  # Column with datetime information
        target="#Passengers",  # Column(s) with time series values to predict
    )
  • Notebooks
  • Google Colab
  • Kaggle
chronos-2-int8-torchao
131 MB
Ctrl+K
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  • 1 contributor
History: 8 commits
oxfrug's picture
oxfrug
Update README.md
f288c67 verified 20 days ago
  • eval
    eval: speed, series MASE, coverage JSON 20 days ago
  • .gitattributes
    1.52 kB
    initial commit 20 days ago
  • README.md
    5.79 kB
    Update README.md 20 days ago
  • config.json
    1.07 kB
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  • fast_infer.py
    3.8 kB
    add fast_infer.py (TF32 + torch.compile) 20 days ago
  • load.py
    2.2 kB
    load.py docstring 20 days ago
  • model.safetensors
    131 MB
    xet
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  • quant_meta.json
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