Instructions to use eugenetanjc/wav2vec_cv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eugenetanjc/wav2vec_cv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eugenetanjc/wav2vec_cv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("eugenetanjc/wav2vec_cv") model = AutoModelForCTC.from_pretrained("eugenetanjc/wav2vec_cv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from eugenetanjc/wav2vec_cv: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/eugenetanjc/wav2vec_cv/resolve/main/training_args.bin
- Command line
-
hf download hf://eugenetanjc/wav2vec_cv/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/eugenetanjc/wav2vec_cv/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- c6e5e2af24116003f699557f0b8a77d4a75f6348f7650204b5d6a3aa1cd885ba
- Size of remote file:
- 2.99 kB
- SHA256:
- 1e8c34aaa5ebd8181bf53e1c8451be515906495a74139bc28d248b711b34934a
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