Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hindi
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use amitkayal/whisper-tiny-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amitkayal/whisper-tiny-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="amitkayal/whisper-tiny-hi")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("amitkayal/whisper-tiny-hi") model = AutoModelForSpeechSeq2Seq.from_pretrained("amitkayal/whisper-tiny-hi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files- config.json +3 -90
- pytorch_model.bin +1 -1
- training_args.bin +1 -1
config.json
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"num_mel_bins": 80,
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],
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"torch_dtype": "float32",
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"transformers_version": "4.26.0.dev0",
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"use_cache":
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"vocab_size": 51865
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}
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"forced_decoder_ids": [
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"num_mel_bins": 80,
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"pad_token_id": 50257,
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"scale_embedding": false,
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"suppress_tokens": [],
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"torch_dtype": "float32",
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"transformers_version": "4.26.0.dev0",
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"use_cache": false,
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"vocab_size": 51865
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 151097331
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version https://git-lfs.github.com/spec/v1
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oid sha256:1fa03a743eb705a1c2ea8e4eb8c963ebae937d4311e2cc4499cc193e7593c145
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size 151097331
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 3567
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version https://git-lfs.github.com/spec/v1
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oid sha256:362e717ec64557e66bd5d8f62fa29aef8fc2ace787027c930d56cf138176c347
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size 3567
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