Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use GFazzito/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GFazzito/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GFazzito/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("GFazzito/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("GFazzito/whisper-tiny") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
- training_args.bin +2 -2
config.json
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"transformers_version": "4.
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"use_cache": false,
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"use_weighted_layer_sum": false,
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"vocab_size": 51865
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"use_weighted_layer_sum": false,
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"vocab_size": 51865
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pytorch_model.bin
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training_args.bin
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