Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
whisper-event
Eval Results (legacy)
Instructions to use sgangireddy/whisper-medium-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgangireddy/whisper-medium-cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sgangireddy/whisper-medium-cs")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sgangireddy/whisper-medium-cs") model = AutoModelForSpeechSeq2Seq.from_pretrained("sgangireddy/whisper-medium-cs") - Notebooks
- Google Colab
- Kaggle
to fix leaderboard I hope
#1
by mikr - opened
README.md
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- generated_from_trainer
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- whisper-event
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datasets:
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- common_voice_11_0
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metrics:
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- wer
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model-index:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_11_0
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type: common_voice_11_0
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config: cs
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split: test
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args: cs
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- generated_from_trainer
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- whisper-event
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: mozilla-foundation/common_voice_11_0
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type: mozilla-foundation/common_voice_11_0
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config: cs
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split: test
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args: cs
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