VaidenceVLM-1.0

VaidenceVLM-1.0 — Research Preview

VaidenceVLM-1.0 is a research-only PEFT/QLoRA adapter for OpenGVLab/InternVL3_5-4B. This repository contains adapter weights, not a standalone 4B base model. It requires the named base model, a CUDA GPU, and trust_remote_code=True.

It is not a medical device and must not be used for diagnosis, triage, treatment, or patient care.

Quick start

git clone https://huggingface.co/dipankar500/VaidenceVLM-1.0
cd VaidenceVLM-1.0
python -m pip install -r requirements.txt
python inference.py --adapter . --image /path/to/image.jpg --question "Describe visible findings and state uncertainty."

SYSTEM_PROMPT.txt is a safety-oriented interactive prompt. It was not used for the reported benchmark scores, so do not prepend it when reproducing those results.

Reproducible generative evaluation — not official leaderboard metrics

Metrics use our released greedy generative evaluator and custom normalized answer matching. They are not official benchmark leaderboard scores, clinical accuracy, evidence of state of the art, or a comparison with Gemini or another proprietary model. See EVALUATION.md.

Repository contents

• adapter_model.safetensors, adapter_config.json: PEFT adapter weights/configuration.
• tokenizer/: recovered tokenizer files.
• inference.py: verified local inference entry point.
• SYSTEM_PROMPT.txt: default interactive research-safety prompt.
• EVALUATION.md, TRAINING_SUMMARY.md, LIMITATIONS.md: transparent release documentation.

Citation

See CITATION.cff. Cite InternVL 3.5 and the original datasets in research use.