Instructions to use cahya/faster-whisper-medium-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/faster-whisper-medium-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cahya/faster-whisper-medium-id")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cahya/faster-whisper-medium-id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f06802f5f8372a0949a78226b722cd2c68477f6c766b336222557d258563e6d9
- Size of remote file:
- 1.53 GB
- SHA256:
- 95849bff3c922bd11c5d96a588a3366e305a5b7c588bbb12ef2381e514b58850
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