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 transcriptions_cv7_validation.json from jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772: direct link, hf CLI and curl.
- Browser
- Download file 15.3 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772/resolve/main/transcriptions_cv7_validation.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772/transcriptions_cv7_validation.json
-
curl -L -o transcriptions_cv7_validation.json https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772/resolve/main/transcriptions_cv7_validation.json
15.3 MB
- Xet hash:
- bc315692304f5a562a3c8d464d142d362ac7409178a2b500659904b87975a87c
- Size of remote file:
- 15.3 MB
- SHA256:
- 0c68f5ca8803d3fb7d28554b610571c6e16cea28935f5a5c26e8531550276c3c
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