Instructions to use ThomasFG/101.25-33.75 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasFG/101.25-33.75 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ThomasFG/101.25-33.75")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ThomasFG/101.25-33.75") model = AutoModelForSpeechSeq2Seq.from_pretrained("ThomasFG/101.25-33.75", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4769a476b13b13ee83116a6d8040364817af1b157da28dcce136b6ede203190
- Size of remote file:
- 967 MB
- SHA256:
- a2f63e331aa45930990453f292cb5a301854e8d5a18c86802bc0bb98424b8d93
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