Instructions to use jonatasgrosman/exp_w2v2t_en_unispeech_s809 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_en_unispeech_s809 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_s809")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech_s809") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech_s809", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_test.json from jonatasgrosman/exp_w2v2t_en_unispeech_s809: direct link, hf CLI and curl.
- Browser
- Download file 74.8 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_en_unispeech_s809/resolve/main/transcriptions_cv7_test.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_en_unispeech_s809/transcriptions_cv7_test.json
-
curl -L -o transcriptions_cv7_test.json https://huggingface.co/jonatasgrosman/exp_w2v2t_en_unispeech_s809/resolve/main/transcriptions_cv7_test.json
74.8 MB
- Xet hash:
- 8f292fbfd4bdb2af804d322b74f0065a10fd70b57def7c78b1e23a450ce71ee6
- Size of remote file:
- 74.8 MB
- SHA256:
- 9d81c25fa1edcd73486029716380626775d458276cb6b4793366a8b1b2879477
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