Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use mike249/whisper-tiny-he-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mike249/whisper-tiny-he-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mike249/whisper-tiny-he-2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mike249/whisper-tiny-he-2") model = AutoModelForSpeechSeq2Seq.from_pretrained("mike249/whisper-tiny-he-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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# Whisper Tiny Hebrew
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the ivrit-ai/whisper-training dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6254
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- Wer: 55.8816
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## Model description
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# Whisper Tiny Hebrew
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the ivrit-ai/whisper-training dataset.
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## Model description
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