Instructions to use hts98/wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hts98/wav2vec2") model = AutoModelForCTC.from_pretrained("hts98/wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hts98/wav2vec2: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/hts98/wav2vec2/resolve/main/training_args.bin
- Command line
-
hf download hf://hts98/wav2vec2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hts98/wav2vec2/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 08afc76917e0d7f3576c08a05ba01d456cb3390888af540dabfa792152717cfb
- Size of remote file:
- 3.96 kB
- SHA256:
- 8dd264fe60e62dbfe1b8b0b08523001488d6935916be31ba1c10e93142373e75
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