Instructions to use ctranslate2-4you/whisper-distil-large-v3.5-ct2-bfloat16 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-bfloat16 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-bfloat16")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ctranslate2-4you/whisper-distil-large-v3.5-ct2-bfloat16", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2121dd22bccc3bc5c7dd2e38312ef409a2458a55f963234f117ecc61ed9596bf
- Size of remote file:
- 1.51 GB
- SHA256:
- 7acd458021a570a9e256e198d91ba8db687518173c6247f0a7c2500f85d4a682
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