Instructions to use jonatasgrosman/exp_w2v2t_en_unispeech_s870 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_en_unispeech_s870 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_s870")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech_s870") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech_s870", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_test.json from jonatasgrosman/exp_w2v2t_en_unispeech_s870: direct link, hf CLI and curl.
- Browser
- Download file 74.3 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_en_unispeech_s870/resolve/main/transcriptions_cv7_test.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_en_unispeech_s870/transcriptions_cv7_test.json
-
curl -L -o transcriptions_cv7_test.json https://huggingface.co/jonatasgrosman/exp_w2v2t_en_unispeech_s870/resolve/main/transcriptions_cv7_test.json
74.3 MB
- Xet hash:
- 559b35e19ec137036005a25e36777b28349226527d024fd4c5d35d8ec3d9da74
- Size of remote file:
- 74.3 MB
- SHA256:
- 28efe4c68ce59b27ad88c684dfafc1024a52f20260fc4a6aea4a70dfc7c41a62
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