Instructions to use MBMMurad/wav2vec2_spec_aug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MBMMurad/wav2vec2_spec_aug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="MBMMurad/wav2vec2_spec_aug")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("MBMMurad/wav2vec2_spec_aug") model = AutoModelForCTC.from_pretrained("MBMMurad/wav2vec2_spec_aug", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MBMMurad/wav2vec2_spec_aug: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/MBMMurad/wav2vec2_spec_aug/resolve/main/training_args.bin
- Command line
-
hf download hf://MBMMurad/wav2vec2_spec_aug/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MBMMurad/wav2vec2_spec_aug/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 94fcd7b77496bbdc6ad7316648ecc03d01d057c69a230e2b52e8252d795a3244
- Size of remote file:
- 3.31 kB
- SHA256:
- 453e207107c871155be18e2993745e39bc9d17f87ec0563b4b3136ebabd1fe4e
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