Instructions to use ThomasFG/0-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasFG/0-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ThomasFG/0-10")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ThomasFG/0-10") model = AutoModelForSpeechSeq2Seq.from_pretrained("ThomasFG/0-10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d44fcacae307823137a1151ca9916fdb965ffe4d73d0a5724effc155baf02da9
- Size of remote file:
- 4.73 kB
- SHA256:
- 6230b4404bd393df75dc4128ba55327e011dd2a2507ee152ac7fef22b3142bf1
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