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dipankar500
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Model Details
Model Provider
dipankar500
Model Tree
OpenGVLab/InternVL3_5-4B
Input Modalities
Output Modalities
Supported Functionality
bash
git clone https://huggingface.co/dipankar500/VaidenceVLM-1.0cd VaidenceVLM-1.0python -m pip install -r requirements.txtpython 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.
| Benchmark / split | Questions | Normalized exact match | Token F1 | Yes/No exact match | Errors |
|---|---|---|---|---|---|
| SLAKE English test | 1061 | 57.49% | 62.33% | 80.85% | 0 |
| VQA-RAD test | 32 | 53.12% | 60.64% | 77.78% | 0 |
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.
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.See CITATION.cff. Cite InternVL 3.5 and the original datasets in research use.