Image-Text-to-Text
Transformers
GGUF
English
smolvlm
vlm
dpo
hallucination-reduction
accessibility
qlora
rlaif
conversational
Instructions to use Cubex11/Solari-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cubex11/Solari-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Cubex11/Solari-GGUF") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Cubex11/Solari-GGUF", dtype="auto") - llama-cpp-python
How to use Cubex11/Solari-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Cubex11/Solari-GGUF", filename="Solari-f16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Cubex11/Solari-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Cubex11/Solari-GGUF:F16 # Run inference directly in the terminal: llama cli -hf Cubex11/Solari-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Cubex11/Solari-GGUF:F16 # Run inference directly in the terminal: llama cli -hf Cubex11/Solari-GGUF:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Cubex11/Solari-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf Cubex11/Solari-GGUF:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Cubex11/Solari-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Cubex11/Solari-GGUF:F16
Use Docker
docker model run hf.co/Cubex11/Solari-GGUF:F16
- LM Studio
- Jan
- vLLM
How to use Cubex11/Solari-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Cubex11/Solari-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Cubex11/Solari-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Cubex11/Solari-GGUF:F16
- SGLang
How to use Cubex11/Solari-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Cubex11/Solari-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Cubex11/Solari-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Cubex11/Solari-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Cubex11/Solari-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Ollama
How to use Cubex11/Solari-GGUF with Ollama:
ollama run hf.co/Cubex11/Solari-GGUF:F16
- Unsloth Studio
How to use Cubex11/Solari-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Cubex11/Solari-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Cubex11/Solari-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Cubex11/Solari-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Cubex11/Solari-GGUF with Docker Model Runner:
docker model run hf.co/Cubex11/Solari-GGUF:F16
- Lemonade
How to use Cubex11/Solari-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Cubex11/Solari-GGUF:F16
Run and chat with the model
lemonade run user.Solari-GGUF-F16
List all available models
lemonade list
| 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](https://huggingface.co/Cubex11/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](https://huggingface.co/Cubex11/Solari). | |
| > [!WARNING] | |
| > `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 | |
| - **Base Model:** [Cubex11/Solari](https://huggingface.co/Cubex11/Solari) | |
| - **Original Base:** [SmolVLM2-500M-Video-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM2-500M-Video-Instruct) | |
| - **Format:** GGUF (for use with llama.cpp, Ollama, LM Studio, etc.) | |
| - **Fine-tuning Method:** QLoRA + DPO on [RLAIF-V](https://huggingface.co/datasets/HuggingFaceH4/rlaif-v_formatted) (72K preference pairs) | |
| - **License:** Apache-2.0 | |
| ## 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 | |
| ```bash | |
| # 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 | |
| ```bash | |
| # Create a Modelfile | |
| echo 'FROM ./Solari.gguf' > Modelfile | |
| ollama create solari -f Modelfile | |
| ollama run solari | |
| ``` | |
| ## Links | |
| - **Full-precision model:** [Cubex11/Solari](https://huggingface.co/Cubex11/Solari) | |
| - **Training dataset:** [RLAIF-V](https://huggingface.co/datasets/HuggingFaceH4/rlaif-v_formatted) | |
| - **Base model:** [SmolVLM2-500M-Video-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM2-500M-Video-Instruct) | |
| ## Citation | |
| ```bibtex | |
| @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} | |
| } | |
| ``` |