Instructions to use naksyu/yui-math-python-qwen35-9b-v0.6-fft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use naksyu/yui-math-python-qwen35-9b-v0.6-fft with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="naksyu/yui-math-python-qwen35-9b-v0.6-fft")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("naksyu/yui-math-python-qwen35-9b-v0.6-fft")
model = AutoModelForCausalLM.from_pretrained("naksyu/yui-math-python-qwen35-9b-v0.6-fft")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use naksyu/yui-math-python-qwen35-9b-v0.6-fft with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "naksyu/yui-math-python-qwen35-9b-v0.6-fft"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "naksyu/yui-math-python-qwen35-9b-v0.6-fft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/naksyu/yui-math-python-qwen35-9b-v0.6-fft

SGLang

How to use naksyu/yui-math-python-qwen35-9b-v0.6-fft 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 "naksyu/yui-math-python-qwen35-9b-v0.6-fft" \
    --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": "naksyu/yui-math-python-qwen35-9b-v0.6-fft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "naksyu/yui-math-python-qwen35-9b-v0.6-fft" \
        --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": "naksyu/yui-math-python-qwen35-9b-v0.6-fft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use naksyu/yui-math-python-qwen35-9b-v0.6-fft with Docker Model Runner:
```
docker model run hf.co/naksyu/yui-math-python-qwen35-9b-v0.6-fft
```

Yui Math Python Qwen3.5 9B v0.6 FFT

Full-parameter SFT of Qwen3.5 9B for Korean math/Python reasoning experiments.

Training

Base model: Qwen/Qwen3.5-9B
Method: full-parameter bf16 SFT
Epochs: 1
Train loss: 0.7942
Mean token accuracy: 0.8338
Training tokens: 11.84M
Hardware: H200 SXM x2

Training Data

Includes Yui/Lime project data plus public Korean reasoning datasets:

drlee1/deepseek-v4-distill-ko-1k
Jongsim/claude-opus-4.6-reasoning-12k-ko-filtered-v2

Some upstream data is synthetic or model-generated. This release is experimental.

Intended Use

Research and local inference for Korean math, Python-assisted reasoning, concise calculation behavior, and reasoning-style experiments.

Limitations

Not a general-purpose assistant replacement. Verify arithmetic, code, and factual outputs before relying on them.

Downloads last month: 22

Safetensors

Model size

9B params

Tensor type

BF16

Model tree for naksyu/yui-math-python-qwen35-9b-v0.6-fft

Base model

Qwen/Qwen3.5-9B-Base

Finetuned

Qwen/Qwen3.5-9B

Finetuned

(480)

this model

naksyu
/

yui-math-python-qwen35-9b-v0.6-fft