Instructions to use hsali/finetune_emo_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsali/finetune_emo_base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("hsali/finetune_emo_base") model = Wav2Vec2ForSpeechClassification.from_pretrained("hsali/finetune_emo_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hsali/finetune_emo_base: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/hsali/finetune_emo_base/resolve/main/training_args.bin
- Command line
-
hf download hf://hsali/finetune_emo_base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hsali/finetune_emo_base/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 4e3240b4fe43a4e93cee0b378945bb55eb1603f3f01bd23d7b392bbf2448b1eb
- Size of remote file:
- 3.52 kB
- SHA256:
- 51b4dd591e76289ea0e2de469fd6e762a2c5954aa9d86e2dc72ee31d6faeface
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