Instructions to use jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929: direct link, hf CLI and curl.
- Browser
- Download file 1.28 GB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_unispeech_s929/resolve/main/pytorch_model.bin
1.28 GB
- Xet hash:
- f5cc0e9eb25d53bd8b7351d5047e281a1e86aa02d9d94eb985fe2d1db3df16a4
- Size of remote file:
- 1.28 GB
- SHA256:
- deceed022193c98764b2ca9c661058631f7107b291bc5ed52a04d6fe303856cf
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