Instructions to use hsali/few_shots_data_1003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsali/few_shots_data_1003 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("hsali/few_shots_data_1003") model = Wav2Vec2ForSpeechClassification.from_pretrained("hsali/few_shots_data_1003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hsali/few_shots_data_1003: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/hsali/few_shots_data_1003/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hsali/few_shots_data_1003/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hsali/few_shots_data_1003/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 4bd3d8223479708bccfdebafcbb30157b1b6133a346777cfb940568ba33127e5
- Size of remote file:
- 378 MB
- SHA256:
- 62067db1fcf9e4f1300b28062fe41eeb0829bcd13992b5f387a5cd554a03cdbd
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