Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use NS-Y/whisper-tiny-he-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NS-Y/whisper-tiny-he-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NS-Y/whisper-tiny-he-5")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NS-Y/whisper-tiny-he-5") model = AutoModelForSpeechSeq2Seq.from_pretrained("NS-Y/whisper-tiny-he-5") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2
by librarian-bot - opened
README.md
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- generated_from_trainer
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datasets:
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- google/fleurs
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model-index:
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- name: Whisper-tiny Hebrew v5 - Nissan Yaron
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results: []
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- generated_from_trainer
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datasets:
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- google/fleurs
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base_model: openai/whisper-tiny
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model-index:
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- name: Whisper-tiny Hebrew v5 - Nissan Yaron
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results: []
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