Instructions to use jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_validation.json from jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459: direct link, hf CLI and curl.
- Browser
- Download file 81.6 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459/resolve/main/transcriptions_cv7_validation.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459/transcriptions_cv7_validation.json
-
curl -L -o transcriptions_cv7_validation.json https://huggingface.co/jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459/resolve/main/transcriptions_cv7_validation.json
81.6 MB
- Xet hash:
- 73d78c190a4eadc0e7753bd9b34b4013c63e3f44a6e4c612dff64c113cb61de4
- Size of remote file:
- 81.6 MB
- SHA256:
- 4c554a6e2866b8a46a4ff0c99fd2f87f29727b9cc4a7e3dc04a1ddb93aee6674
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