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opscribe-captioner-merged-v1
rbryant19/opscribe-captioner-merged-v1
opscribe-captioner-merged-v1 is a text generation model from rbryant19. Use it when you need the model to write or continue text. It is set up for peft.
LoRA adapter for Qwen2.5-VL-72B-Instruct — surgical frame captioning for the OpScribe pipeline.
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At a glance
- Task
- Text Generation
- Library
- peft
- Access
- Public
- Created
- Mar 18, 2026
- Updated
- Mar 24, 2026
- SHA
- 1493a483
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Base models
Model card
From the Hugging Face model README
OpScribe Captioner Combined v1
LoRA adapter for Qwen2.5-VL-72B-Instruct — surgical frame captioning for the OpScribe pipeline.
Training
- Base model: Qwen/Qwen2.5-VL-72B-Instruct
- Dataset: EgoSurgery (9,618 frames) + surgeon-narrated voiceover dataset (3,402 frames, 3x weighted)
- Total training examples: 13,020 train / 1,893 val
- Framework: Custom PyTorch training loop, LoRA rank=16, alpha=32, lr=2e-4
- Epochs: 3 (24h on 4x NVIDIA H200 140GB)
- Best val_loss: 0.1046
- Hardware: CHTC bhaskargpu4000
Usage
from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
from peft import PeftModel
base = Qwen2VLForConditionalGeneration.from_pretrained(
"Qwen/Qwen2.5-VL-72B-Instruct", device_map="auto"
)
model = PeftModel.from_pretrained(base, "rbryant19/opscribe-captioner-merged-v1")
processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-72B-Instruct")
Framework versions
- PEFT 0.18.1
- Task
- Text Generation
- Library
- peft
- Created
- Mar 18, 2026
- Updated
- Mar 24, 2026