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:
- a6a55ff866b708c8199b6508e268d74b96ec3069f268c15d89361ae78afcd7e5
- Size of remote file:
- 14.3 kB
- SHA256:
- a802e14c07c19bcf4453e75c0cb27403d5e9adaeca746d74a61284db1580a003
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