Instructions to use openai/whisper-large-v3-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-large-v3-turbo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large-v3-turbo")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("openai/whisper-large-v3-turbo") model = AutoModelForMultimodalLM.from_pretrained("openai/whisper-large-v3-turbo") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d3332ff3e0ecf1b73a32ee9e022197ae23790a5e18f44811a317def38eef4a6
- Size of remote file:
- 1.62 GB
- SHA256:
- 542566a422ae4f3fd23f1ba11add198fca01bbf82e66e6a2857b3f608b1eb9d1
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