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Adding more information regarding load_model #16

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Adding more information regarding load_model #16

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Adding more information regarding load_model
maziyarpanahi Nov 16, 2022
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Merge branch 'main' into main
maziyarpanahi Dec 9, 2022
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Merge branch 'paperswithcode:main' into main
maziyarpanahi Dec 10, 2022
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Merge branch 'main' into main
maziyarpanahi Jan 13, 2023
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5 changes: 5 additions & 0 deletions README.md
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Expand Up @@ -51,6 +51,11 @@ model.generate("Scaled dot product attention:\n\n\\[")
# Scaled dot product attention:\n\n\\[ \\displaystyle\\text{Attention}(Q,K,V)=\\text{softmax}(\\frac{QK^{T}}{\\sqrt{d_{k}}}%\n)V \\]
```

The `load_model()` function accepts the following parameters:
- `name: str` that accepts `mini`, `base`, `standard`, `large`, and `huge`
- `dtype: str=None` that accepts `float16` (or when the name is set to `huge`) and `float32`
- `num_gpus: int=None` that accepts the total number of GPUs to be used (by default this is `8`)

Read the full introduction to Galactica models as a [PDF](https://github.com/paperswithcode/galai/blob/main/notebooks/Introduction%20to%20Galactica%20Models.pdf) or a [jupyter notebook](https://github.com/paperswithcode/galai/blob/main/notebooks/Introduction%20to%20Galactica%20Models.ipynb).

You can also find all the model weights with their model cards and inference widget in the [Hugging Face Hub](https://huggingface.co/models?other=galactica). All the models can be used out of the box with the `transformers` library.
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