Instructions to use lmh2011/w2v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmh2011/w2v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lmh2011/w2v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lmh2011/w2v2") model = AutoModelForCTC.from_pretrained("lmh2011/w2v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from lmh2011/w2v2: direct link, hf CLI and curl.
- Browser
- Download file 31 Bytes
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https://huggingface.co/lmh2011/w2v2/resolve/main/README.md
- Command line
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hf download hf://lmh2011/w2v2/README.md
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curl -L -o README.md https://huggingface.co/lmh2011/w2v2/resolve/main/README.md
31 Bytes
metadata
license: apache-2.0