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", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

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
```

Qwen-Templates-Rebuild-Project / README.md

StableQuant

Update README.md

d21ee17 verified 2 months ago

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metadata

license: apache-2.0
base_model:
  - Qwen/Qwen3.6-27B
  - Qwen/Qwen3.6-35B-A3B
  - Qwen/Qwen3.5-27B
  - Qwen/Qwen3.5-35B-A3B
pipeline_tag: text-generation
library_name: transformers
tags:
  - chat-template
  - jinja
  - jinja2
  - qwen3
  - template-fix
  - bugfix

09.06.2026

This project is on hold now. For most stable experience currently, please use https://huggingface.co/spiritbuun/buun-Qwen3.6-chat_template

Preserve Thinking:

To enable preserve-thinking (Agent can remember what he thought about in older turns) pass the following parameter to llama.cpp startup: On Linux&MacOS (Windows need slightly different which cant be correctly displayed here...): --chat-template-kwargs '{"preserve_thinking": true}'

OpenCode:

If using OpenCode do notice they have an open bug for showing thinking content as plain text. Open Bug since 4 months(https://github.com/anomalyco/opencode/issues/11439). Meanwhile you can use the llama.cpp Server switch to hide thinking completely(but still let the model think) using the additonal llama.cpp parameter: --reasoning-format deepseek