Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-medium")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-medium") - Notebooks
- Google Colab
- Kaggle
sanchit-gandhi commited on
Commit ·
0d49445
1
Parent(s): 409c908
Add Flax weights
Browse files- config.json +1 -1
- flax_model.msgpack +3 -0
- generation_config.json +1 -1
config.json
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 51865
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}
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"torch_dtype": "float32",
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"transformers_version": "4.27.0.dev0",
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"use_cache": true,
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"vocab_size": 51865
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}
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flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:9b4f5a77be626930646bdada78929b70771519e34139a6ede1733785f5d7f747
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size 3055465603
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generation_config.json
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"transcribe": 50359,
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"translate": 50358
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},
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"transformers_version": "4.
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}
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"transcribe": 50359,
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"translate": 50358
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},
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"transformers_version": "4.27.0.dev0"
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}
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