Instructions to use jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_test.json from jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784: direct link, hf CLI and curl.
- Browser
- Download file 78.9 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784/resolve/main/transcriptions_cv7_test.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784/transcriptions_cv7_test.json
-
curl -L -o transcriptions_cv7_test.json https://huggingface.co/jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784/resolve/main/transcriptions_cv7_test.json
78.9 MB
- Xet hash:
- 592d470a88696a245e359028b03ec7b0ba98127e2cb27d628edcffee7a9991d9
- Size of remote file:
- 78.9 MB
- SHA256:
- 18293be1aa0548aafe0a43dccc922dc8ca06f7a592f854ba90374b0aab50bb23
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