Instructions to use jonatasgrosman/exp_w2v2t_fa_unispeech_s211 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_fa_unispeech_s211 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_fa_unispeech_s211")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_fa_unispeech_s211") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_fa_unispeech_s211", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transcriptions_cv7_validation.json from jonatasgrosman/exp_w2v2t_fa_unispeech_s211: direct link, hf CLI and curl.
- Browser
- Download file 19.4 MB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_fa_unispeech_s211/resolve/3427e4dbc97d0be74afede6f79d624eaf6ec2c95/transcriptions_cv7_validation.json
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_fa_unispeech_s211@3427e4dbc97d0be74afede6f79d624eaf6ec2c95/transcriptions_cv7_validation.json
-
curl -L -o transcriptions_cv7_validation.json https://huggingface.co/jonatasgrosman/exp_w2v2t_fa_unispeech_s211/resolve/3427e4dbc97d0be74afede6f79d624eaf6ec2c95/transcriptions_cv7_validation.json
19.4 MB
- Xet hash:
- 21b5be4dfbd53c5524d1da546d3793d4bc44864b6b75e26e2ffc25f196c328fd
- Size of remote file:
- 19.4 MB
- SHA256:
- 3400facac5f65d869fcc46beadc30010fa1ee9edcef823e6ae76fc46876142af
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