Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use shimonbh/stt-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shimonbh/stt-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shimonbh/stt-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shimonbh/stt-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("shimonbh/stt-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Checkpoint at step 4000
Browse files
README.md
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library_name: transformers
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license: apache-2.0
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base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_17_0
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model-index:
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- name: stt-small
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results: []
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---
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base_model: openai/whisper-small
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datasets:
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- common_voice_17_0
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library_name: transformers
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: stt-small
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results: []
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