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metadata
library_name: transformers
tags:
  - smolvlm
  - vlm
  - dpo
  - hallucination-reduction
  - accessibility
  - qlora
  - rlaif
  - gguf
license: apache-2.0
language:
  - en
pipeline_tag: image-text-to-text
base_model: Cubex11/Solari

Solari-GGUF

GGUF quantized version of Solari — a 500M parameter vision-language model fine-tuned for reduced hallucination on real-world images.

For full model details, training procedure, and benchmark analysis, see the Solari model card.

Solari-f16.gguf and Solari_v2-f16.gguf are deprecated. Please use Solari_v3-f16.gguf for the best results. Older versions may produce incorrect or degraded outputs.

Model Details

Benchmark Results

Solari improves on 7 out of 8 benchmarks vs the base model:

Benchmark Base Solari Change
POPE Overall 82.67 85.08 +2.41
POPE Recall 76.73 85.33 +8.60
AMBER Avg 79.38 79.77 +0.39
A-OKVQA 68.12 69.00 +0.88
MMStar 38.33 39.60 +1.27
MMBench 53.14 53.42 +0.28
RealWorldQA 49.80 50.59 +0.78
HallusionBench 27.58 28.14 +0.56
MME Perception 1216 1119 -97.7

Note: Benchmarks were evaluated on the full-precision model. GGUF quantization may cause minor performance differences.

Usage

With llama.cpp

# Download the GGUF file
huggingface-cli download Cubex11/Solari-GGUF --local-dir ./solari-gguf

# Run inference
./llama-cli -m ./solari-gguf/Solari.gguf -p "Describe this image" --image your_image.jpg

With Ollama

# Create a Modelfile
echo 'FROM ./Solari.gguf' > Modelfile
ollama create solari -f Modelfile
ollama run solari

Links

Citation

@misc{solari2026,
    title={Solari: Hallucination-Reduced Vision Language Model via QLoRA DPO on RLAIF-V},
    author={Cubex11},
    year={2026},
    url={https://huggingface.co/Cubex11/Solari}
}