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
| python create_student_model.py \ | |
| --teacher_checkpoint "openai/whisper-large-v2" \ | |
| --encoder_layers 32 \ | |
| --decoder_layers 2 \ | |
| --save_dir "./distil-large-v2-init" |