Instructions to use jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772 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-ml_s772 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-ml_s772")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772: direct link, hf CLI and curl.
- Browser
- Download file 1.28 GB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772/resolve/main/pytorch_model.bin
1.28 GB
- Xet hash:
- cf1db173b854d73b0020352b11b302f61b84da3d891840bbc281c786a307624b
- Size of remote file:
- 1.28 GB
- SHA256:
- a75499453eaffad1325b18f98b5ccb7813b87970fa874efb9d0cd67101569cbc
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