Instructions to use jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_validation.json from jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295: direct link, hf CLI and curl.
- Browser
- Download file 4.53 MB
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https://huggingface.co/jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295/resolve/main/transcriptions_cv7_validation.json
- Command line
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hf download hf://jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295/transcriptions_cv7_validation.json
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curl -L -o transcriptions_cv7_validation.json https://huggingface.co/jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s295/resolve/main/transcriptions_cv7_validation.json
4.53 MB
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