Instructions to use ahnaf1393/ORENA_weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ahnaf1393/ORENA_weights with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
ORENA SurgVidLM HEICO + LapChole Adapter
This repository contains the ORENA LoRA adaptation of SurgVidLM for
single-frame surgical visual question answering. The adapter was trained
jointly on HEICO and LapChole and is stored under surgvidLM/.
Base model
The required base checkpoint is the surgvidlm-stage2 subfolder of
jwang01/surgvidlm. This
repository contains only the downstream LoRA adapter; it does not redistribute
the SurgVidLM base weights or training datasets.
Training data
The converted data contained:
- Training: 7,200 HEICO and 5,182 LapChole examples
- Validation: 800 HEICO and 566 LapChole examples
No images, videos, annotations, or other training data are included in this repository.
Adapter details
- Fine-tuning method: LoRA supervised fine-tuning
- LoRA rank: 8
- LoRA alpha: 16
- LoRA dropout: 0.05
- Vision tower: frozen
- Multimodal projector: frozen
- Learning rate: 5e-5
- Epochs: 3
- Effective training batch size: 32
- Seed: 42
- Framework: LLaMA-Factory / PEFT
The selected adapter corresponds to checkpoint 700. The identical adapter is
stored at the training output root because load_best_model_at_end was
enabled.
Validation
- Combined HEICO + LapChole validation loss: 0.3538476527
- Training loss: 0.3713347467
These are loss values, not official-test accuracy scores. Official test-set results should be reported separately when available.
Download
hf download ahnaf1393/ORENA_weights \
--include "surgvidLM/*" \
--local-dir ORENA_weights
hf download jwang01/surgvidlm \
--include "surgvidlm-stage2/*" \
--local-dir surgvidlm_base
Inference with the ORENA SurgVidLM script
python SurgVidLM/frame_vqa_inference_batch.py \
--model-path surgvidlm_base/surgvidlm-stage2 \
--adapter-path ORENA_weights/surgvidLM \
--data-path PATH_TO_INPUT.json \
--result-path predictions.json
Intended use and limitations
This adapter is intended for research on surgical-scene understanding and frame-level visual question answering. It has not been validated as a medical device and must not be used for diagnosis, clinical decisions, or autonomous surgical control.
Performance may vary across procedures, hospitals, imaging systems, patient populations, question formats, and conditions not represented during training.
License
Public redistribution terms are pending confirmation from the SurgVidLM model authors and the applicable HEICO and LapChole data-use agreements. Do not treat the absence of a license field as permission for unrestricted use or redistribution.
Acknowledgements
This adapter is derived from
SurgVidLM. See also the
SurgVidLM paper.
- Downloads last month
- -
Model tree for ahnaf1393/ORENA_weights
Base model
jwang01/surgvidlm