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:
- 627740b00eed88de501bf17103d94b5353ca80b638f2ab0da242aad8c3b0327d
- Size of remote file:
- 3.02 GB
- SHA256:
- 03c8916ea30d27e6e8ee3d3b505ea528c00241aeedded4b6f8ef3c5150cd6d0d
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