Instructions to use jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_validation.json from jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51: direct link, hf CLI and curl.
- Browser
- Download file 81.1 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51/resolve/main/transcriptions_cv7_validation.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51/transcriptions_cv7_validation.json
-
curl -L -o transcriptions_cv7_validation.json https://huggingface.co/jonatasgrosman/exp_w2v2t_fr_unispeech-ml_s51/resolve/main/transcriptions_cv7_validation.json
81.1 MB
- Xet hash:
- 76a37b6a97d8e38a1c450f54114ca31dc668108ee7f3fee991cff3f2c2e0003e
- Size of remote file:
- 81.1 MB
- SHA256:
- 0cc2c9b3f3f8a93810ec1634cdcdd01f7f0407a998b446148ea9a5cab912c67e
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