Instructions to use yip-i/wav2vec2_large_copy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yip-i/wav2vec2_large_copy with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("yip-i/wav2vec2_large_copy") model = AutoModelForPreTraining.from_pretrained("yip-i/wav2vec2_large_copy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from yip-i/wav2vec2_large_copy: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/yip-i/wav2vec2_large_copy/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://yip-i/wav2vec2_large_copy/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/yip-i/wav2vec2_large_copy/resolve/main/flax_model.msgpack
1.27 GB
- Xet hash:
- f4b74e31e6387bfb1fdf377f95ac7266ede8bc7ed2361fd3e323ea5ca2296f52
- Size of remote file:
- 1.27 GB
- SHA256:
- c0455bda4e815ef49ee78fbcbd0903f603b81f16fc73438136de33b35cc3ebda
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