Instructions to use hsali/m_seq_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsali/m_seq_1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("hsali/m_seq_1") model = Wav2Vec2ForSpeechClassification.from_pretrained("hsali/m_seq_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hsali/m_seq_1: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/hsali/m_seq_1/resolve/main/training_args.bin
- Command line
-
hf download hf://hsali/m_seq_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hsali/m_seq_1/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- f35343fb97d88574c2c04803855d4eaf84bb0fc545e971daf57b0c202d67748d
- Size of remote file:
- 3.45 kB
- SHA256:
- c085e2eb88ad757553b1d5129e19d3a03afa3e277806bddba56f4bcefe41ac14
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