How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cgalabs/yks-vlm-lora-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cgalabs/yks-vlm-lora-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/cgalabs/yks-vlm-lora-v2
Quick Links

YKS-VLM-LoRA-v2

YKS-VLM-LoRA-v2 is a LoRA fine-tuned Vision-Language Model built on top of
Qwen2.5-VL-32B-Instruct, optimized for Turkish exam-style math questions (YKS).

This model is designed as a vision-to-structured-output component rather than a full end-to-end solver.

check us out: cga-labs.com


What this model is good at

  • Reading math questions from images
  • Understanding exam-style layouts (options, figures, tables)
  • Producing stable, structured JSON outputs
  • Acting as a preprocessing / parsing layer for downstream solvers

Typical output format:

{
  "final_answer": "C"
}
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