Image-Text-to-Text
PEFT
Safetensors
medical
vision-language
surgical-ai
pituitary-surgery
bounding-box
deprecated
conversational
Instructions to use mmrech/pitvqa-qwen2vl-bbox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mmrech/pitvqa-qwen2vl-bbox with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-2B-Instruct") model = PeftModel.from_pretrained(base_model, "mmrech/pitvqa-qwen2vl-bbox") - Notebooks
- Google Colab
- Kaggle
PitVQA BBox Model (Deprecated)
Note: This is an earlier single-task model. For production use, see pitvqa-qwen2vl-unified-v2 which includes bbox detection plus more capabilities.
Description
Early version fine-tuned for bounding box detection only. Outputs:
<box x1='20' y1='30' x2='60' y2='70'>target</box>
Recommended Alternative
Use the unified model instead:
- pitvqa-qwen2vl-unified-v2 - Multi-task (point, bbox, classification)
- pitvqa-qwen2vl-merged - Ready-to-use deployment
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