Instructions to use ducha07/wav2vec2-ASR3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ducha07/wav2vec2-ASR3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ducha07/wav2vec2-ASR3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ducha07/wav2vec2-ASR3") model = AutoModelForCTC.from_pretrained("ducha07/wav2vec2-ASR3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ducha07/wav2vec2-ASR3: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/ducha07/wav2vec2-ASR3/resolve/main/training_args.bin
- Command line
-
hf download hf://ducha07/wav2vec2-ASR3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ducha07/wav2vec2-ASR3/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 003d20f272ccebefb2d6d77b3415f5ffdf548fcc3414ba24e762ecfbff4e152c
- Size of remote file:
- 4.66 kB
- SHA256:
- f4e3014dbb5317d28463b519ce5aaef0c957d7f39e0ea1eba759b4c86f28aa97
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