Instructions to use TencentGameMate/chinese-wav2vec2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TencentGameMate/chinese-wav2vec2-base with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("TencentGameMate/chinese-wav2vec2-base") model = AutoModelForPreTraining.from_pretrained("TencentGameMate/chinese-wav2vec2-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TencentGameMate/chinese-wav2vec2-base: direct link, hf CLI and curl.
- Browser
- Download file 380 MB
-
https://huggingface.co/TencentGameMate/chinese-wav2vec2-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TencentGameMate/chinese-wav2vec2-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TencentGameMate/chinese-wav2vec2-base/resolve/main/pytorch_model.bin
380 MB
- Xet hash:
- 54150325f05c9fb9b3876e0470ce0fabb75605a67a19a6f7f8b542591868161e
- Size of remote file:
- 380 MB
- SHA256:
- be2da40c9e7ae26bfc904a3ed79ebb9e8f060bec6dba85d6a6ae86114bc38901
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