Instructions to use ctranslate2-4you/whisper-distil-large-v3.5-ct2-float32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctranslate2-4you/whisper-distil-large-v3.5-ct2-float32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ctranslate2-4you/whisper-distil-large-v3.5-ct2-float32")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ctranslate2-4you/whisper-distil-large-v3.5-ct2-float32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e493f4be2d973d040d05114e72811b77db89ead480d8eb0e1230c7d93aff737
- Size of remote file:
- 3.03 GB
- SHA256:
- e0323c86f2b57b3072d615afaf08aeac9163d6371f037c2d171179c61047c5ed
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