Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
German
whisper
Eval Results (legacy)
Instructions to use sanchit-gandhi/distil-whisper-large-v3-de-kd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanchit-gandhi/distil-whisper-large-v3-de-kd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sanchit-gandhi/distil-whisper-large-v3-de-kd")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sanchit-gandhi/distil-whisper-large-v3-de-kd") model = AutoModelForSpeechSeq2Seq.from_pretrained("sanchit-gandhi/distil-whisper-large-v3-de-kd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 191 Bytes
264a841 | 1 2 3 4 5 6 7 8 9 | #!/usr/bin/env bash
python create_student_model.py \
--teacher_checkpoint "openai/whisper-large-v3" \
--encoder_layers 32 \
--decoder_layers 2 \
--save_dir "./distil-large-v3-init"
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