Instructions to use tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 100
Browse files- model.safetensors +1 -1
- training_args.bin +1 -1
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