jamesjk4242/insighta-mandala-v13

Insighta Mandala v13

Fine-tuned Qwen3-4B model for generating mandala learning plans in JSON format.

Model Details

• Base model: Qwen/Qwen3-4B
• Fine-tuning: LoRA on mandala learning plan generation task
• Languages: Korean, English
• Output format: Structured JSON (mandala chart format)

Available Quantizations

Format	Size	Description
model.safetensors	~8GB	Full F16 weights
insighta-mandala-v13-Q8_0.gguf	~4GB	Q8_0 quantized GGUF
insighta-mandala-v13-Q4_K_M.gguf	~2.4GB	Q4_K_M quantized GGUF (recommended for CPU)

Usage

With llama-cpp-python

from llama_cpp import Llama

llm = Llama(model_path="insighta-mandala-v13-Q4_K_M.gguf", n_ctx=4096)
output = llm(
    "<|im_start|>user\nTOEFL 100점 만다라트 차트를 만들어줘<|im_end|>\n<|im_start|>assistant\n",
    max_tokens=2048,
    temperature=0.7,
)
print(output["choices"][0]["text"])

With HF Space API

curl -X POST https://jamesjk4242-insighta-mandala-v13-api.hf.space/api/predict \
  -H "Content-Type: application/json" \
  -d '{"data": ["TOEFL 100점 만다라트 차트를 만들어줘", "You are a helpful assistant that generates mandala learning plans in JSON format.", 2048, 0.7, 0.9, true]}'