Instructions to use charris/wav2vec_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use charris/wav2vec_adapter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="charris/wav2vec_adapter")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("charris/wav2vec_adapter") model = AutoModelForCTC.from_pretrained("charris/wav2vec_adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from charris/wav2vec_adapter: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/charris/wav2vec_adapter/resolve/main/training_args.bin
- Command line
-
hf download hf://charris/wav2vec_adapter/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/charris/wav2vec_adapter/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 8c577db4be490153b3600f19e843c3c6645454770f37cdf8de90d1ea5945273c
- Size of remote file:
- 4.92 kB
- SHA256:
- 5d86d5db302f796ca22eb89cd1729b8bd4609edb23b70e89ec9b2a185c4690e8
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