Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use fontadie/whisper-tiny-openslrdev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fontadie/whisper-tiny-openslrdev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fontadie/whisper-tiny-openslrdev")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("fontadie/whisper-tiny-openslrdev") model = AutoModelForSpeechSeq2Seq.from_pretrained("fontadie/whisper-tiny-openslrdev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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DS-PM4-FS24/whisper-tiny-tedlium
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initial commit
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