Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Russian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use lorenzoncina/whisper-medium-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lorenzoncina/whisper-medium-ru with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lorenzoncina/whisper-medium-ru")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("lorenzoncina/whisper-medium-ru") model = AutoModelForSpeechSeq2Seq.from_pretrained("lorenzoncina/whisper-medium-ru", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
656efa7
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Parent(s): b047ce1
Update metadata with huggingface_hub
Browse files
README.md
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- name: Whisper Medium Russian
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results:
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- task:
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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 ru
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type: mozilla-foundation/common_voice_11_0
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split: test
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args: ru
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metrics:
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type: wer
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value: 7.562437929892964
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- name: Whisper Medium Russian
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: mozilla-foundation/common_voice_11_0 ru
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type: mozilla-foundation/common_voice_11_0
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split: test
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args: ru
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metrics:
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- type: wer
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value: 7.562437929892964
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name: Wer
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: google/fleurs
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type: google/fleurs
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config: ru_ru
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split: test
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metrics:
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- type: wer
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value: 10.92
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name: WER
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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