Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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pipeline_tag: automatic-speech-recognition
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license: apache-2.0
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---
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metrics:
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value: 5.008769117619326
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value: 1.284936273212057
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pipeline_tag: automatic-speech-recognition
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license: apache-2.0
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---
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