Instructions to use lgris/distil-whisper-large-v2-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgris/distil-whisper-large-v2-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lgris/distil-whisper-large-v2-pt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("lgris/distil-whisper-large-v2-pt") model = AutoModelForSpeechSeq2Seq.from_pretrained("lgris/distil-whisper-large-v2-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c153fcf3d09c4f21b0e2cd8f4e624511363f4263b3edc6f394bda6af8475887
- Size of remote file:
- 1.06 kB
- SHA256:
- 2d3c4e38f00e8e34efe125975501971b099ba874ae1c1bfe1505830dfdc2d30f
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