Whisper Large-v3 Medical

This model is a fine-tuned version of openai/whisper-large-v3 on medical speech data. It is trained for Automatic Speech Recognition (ASR) of doctor-patient dialogues and medical narratives, with support for English and Arabic.

🩺 Use Cases

  • Transcribing clinical interviews.
  • Building medical dictation tools.
  • Precision: float16 (better for inference), float32 (better for fine-tuning)

πŸ“Š Performance

  • **WER (Word Error Rate): 4.12% **
  • Optimized for clean and domain-specific spoken medical data.

πŸ”§ Model Details

πŸ§ͺ How to Use

from transformers import WhisperProcessor, WhisperForConditionalGeneration

model_id = "yehiazak/whisper-largev3-medical"

# Load FP16 model
model = WhisperForConditionalGeneration.from_pretrained(model_id, revision="fp16")

# Load FP32 model
model = WhisperForConditionalGeneration.from_pretrained(model_id)

processor = WhisperProcessor.from_pretrained(model_id)
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