Instructions to use ducha07/wav2vec2-ASR5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ducha07/wav2vec2-ASR5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ducha07/wav2vec2-ASR5")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ducha07/wav2vec2-ASR5") model = AutoModelForCTC.from_pretrained("ducha07/wav2vec2-ASR5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ducha07/wav2vec2-ASR5: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/ducha07/wav2vec2-ASR5/resolve/main/training_args.bin
- Command line
-
hf download hf://ducha07/wav2vec2-ASR5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ducha07/wav2vec2-ASR5/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 34606301c60d0091134f0f196e3c85d2f06ac0789135fedc6ac7883a5e216b0f
- Size of remote file:
- 4.73 kB
- SHA256:
- 4c9f559a8b24ddfcf19cadc5c250933c0428f0014e22bc62338fc74f8db203ed
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