Instructions to use jonatasgrosman/exp_w2v2t_id_unispeech_s149 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_id_unispeech_s149 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_id_unispeech_s149")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_id_unispeech_s149") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_id_unispeech_s149", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_validation.json from jonatasgrosman/exp_w2v2t_id_unispeech_s149: direct link, hf CLI and curl.
- Browser
- Download file 11.3 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_id_unispeech_s149/resolve/main/transcriptions_cv7_validation.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_id_unispeech_s149/transcriptions_cv7_validation.json
-
curl -L -o transcriptions_cv7_validation.json https://huggingface.co/jonatasgrosman/exp_w2v2t_id_unispeech_s149/resolve/main/transcriptions_cv7_validation.json
11.3 MB
- Xet hash:
- 6e3569e33fc1b0bd5692edf759b78972a2174cd2dbbea8d9b33d35aa3361ed7f
- Size of remote file:
- 11.3 MB
- SHA256:
- d37624bf472983ab054ca23c32aaefcd87a2aee627b009db1bf2c2035b6c2196
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