Instructions to use facebook/mms-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-300m with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("facebook/mms-300m") model = AutoModelForPreTraining.from_pretrained("facebook/mms-300m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/mms-300m: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/facebook/mms-300m/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/mms-300m/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/mms-300m/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- a46512fc0394234fc5515726e2b751abcdf7fe0430f89c0029e1656b84b51fa0
- Size of remote file:
- 1.27 GB
- SHA256:
- b20cf117906cdbe67b4bc364b4e620a0a7bd7dbe8ccf01214c1dd14e2c46f39e
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