Instructions to use jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jonatasgrosman/exp_w2v2t_ja_unispeech-ml_s728/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- 42b8260a92cfba3b1d184b9f6f588c572d076c60dec2d328de8b577ba59a66e5
- Size of remote file:
- 1.27 GB
- SHA256:
- 1d3692661ab88ab8abf549ac49630903caab4fc347016567c5c812ba3d7c67a8
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