Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Russian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use internalhell/whisper_small_ru_model_trainer_3ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internalhell/whisper_small_ru_model_trainer_3ep with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="internalhell/whisper_small_ru_model_trainer_3ep")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("internalhell/whisper_small_ru_model_trainer_3ep") model = AutoModelForSpeechSeq2Seq.from_pretrained("internalhell/whisper_small_ru_model_trainer_3ep", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Whisper Small ru - slowlydoor
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
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It achieves the following results on the evaluation set:
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# Whisper Small ru - slowlydoor ([Automatic Speech Recognition](https://github.com/SlowlyDoor/Automatic-Speech-Recognition))
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
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It achieves the following results on the evaluation set:
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