Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload FlaxWhisperForConditionalGeneration
d284551
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Update config.json to suppress task tokens (#10)
- Update config.json to suppress task tokens (235da5827987d58d18cbddf5b9d39b93e9af19dc) Co-authored-by: Guillaume Klein <guillaumekln@users.noreply.huggingface.co>3a57fe6
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Add Flax weights
sanchit-gandhi3025605
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Allow single quotes "'" and hyphens "-" (#3)
- Allow single quotes "'" and hyphens "-" (a5796832d706e2ccafe86bdf823d50b75b4a6b2c) Co-authored-by: Sanchit Gandhi <sanchit-gandhi@users.noreply.huggingface.co>5ab69db
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Update `max_length` param
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Upload config
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Upload config
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Upload config
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Upload config
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Upload config
6dadadd
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Upload WhisperForConditionalGeneration
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Upload config
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Upload config
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Upload WhisperForConditionalGeneration
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Upload model
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