Instructions to use ThomasFG/0-101.25-33.75 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasFG/0-101.25-33.75 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ThomasFG/0-101.25-33.75")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ThomasFG/0-101.25-33.75") model = AutoModelForSpeechSeq2Seq.from_pretrained("ThomasFG/0-101.25-33.75", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 169e330c2dbc27307a36046184a91beff3b868dacc3954ea9d515113bb31b187
- Size of remote file:
- 967 MB
- SHA256:
- ccb06aa2b9dbbd75c1f02a84e2492b187c24e33b75d73e5770a4cf2ddeae6b9a
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