Instructions to use StableQuant/Qwen-Templates-Rebuild-Project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use StableQuant/Qwen-Templates-Rebuild-Project with Transformers:

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

pipe = pipeline("text-generation", model="StableQuant/Qwen-Templates-Rebuild-Project")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("StableQuant/Qwen-Templates-Rebuild-Project", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use StableQuant/Qwen-Templates-Rebuild-Project with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "StableQuant/Qwen-Templates-Rebuild-Project"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "StableQuant/Qwen-Templates-Rebuild-Project",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/StableQuant/Qwen-Templates-Rebuild-Project

SGLang

How to use StableQuant/Qwen-Templates-Rebuild-Project 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 "StableQuant/Qwen-Templates-Rebuild-Project" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "StableQuant/Qwen-Templates-Rebuild-Project",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "StableQuant/Qwen-Templates-Rebuild-Project" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "StableQuant/Qwen-Templates-Rebuild-Project",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use StableQuant/Qwen-Templates-Rebuild-Project with Docker Model Runner:
```
docker model run hf.co/StableQuant/Qwen-Templates-Rebuild-Project
```

22.05 Tool Calling, Reasoning and agentic behaviour has been updated, potential edge case fixes also included now.

Everything should work fine now. Agentic Coding works fine, Toolcall errors are now correctly catched and handled.

TL:DR Download your fixed and finally working Qwen3.5 and Qwen3.6 jinja chat-template here. V1.1.2 with new tool call error bug fixes and additional edge case enhancements is now released.

You can use this template for any Qwen3 model (only Qwen3-Coder has another template format) Compatible with Qwen3, Qwen3.5 and Qwen3.6 in any OpenWeight size yet released!

Update: V1.1.2 is out in the wild now!

Additional fixes to tool calling have been done, verified correct developer role handling and other improvements. I would consider this a first stable version.

Welcome to the Template Rebuild Project

How do we got here: Annoyed from various bugs with Qwen3.5 and Qwen 3.6 models tool calling etc. I decided to test many different community variants of Qwen Templates, like probably many others out there. At the moment there isnt any completly working chat template for the Qwen3.5 and Qwen3.6 models.

Community patches were collected and patched together to made a single final version. But it still contained bugs.

In the spirit and effort of froggeric https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates/ I want to make this awesome model category useful for any case.

So I did intense preresearch about the models nature, collected a huge list of commonly used ai-tools and which requests do they make to LLM-Endpoints.

All of this was then fed into a new, from the ground up built version of a chat-template.

I believe I did that groundwork, currently I didnt covered all off the over 90 common AI-tools but only like 30, I will continue to enhance the information pile and get 99% tool coverage(100% is probably unnecessary and impossible, considering the fast evolving environment, also many tools use the same calling mechanisms).

This will lead to a final version of the file that is useable for any usecase you can think of.

Currently a third version is released as v1.1.2 which I would call stable

65 specific tests has been run and actual behaviour also manually verified by me.

Please feel free to report any bug you encounter with the template, it will be looked in manually from me and be analyzed and fixed.

Have fun!

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