Instructions to use hsali/few_shots_data_1002 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsali/few_shots_data_1002 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("hsali/few_shots_data_1002") model = Wav2Vec2ForSpeechClassification.from_pretrained("hsali/few_shots_data_1002", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hsali/few_shots_data_1002: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/hsali/few_shots_data_1002/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hsali/few_shots_data_1002/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hsali/few_shots_data_1002/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 0fa133d6d174bbd37736b011160af2655994a0d6a495e32dde0271809b23e31e
- Size of remote file:
- 378 MB
- SHA256:
- 8a682c5a9c61ae55a55a162b9292a842d7dee841365e514932e3172174e93f09
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