Text Generation
Transformers
Safetensors
qwen3.6
quantized
int4
w4a16
autoround
text-only
tool-calling
mtp
speculative-decoding
agent
vllm
single-gpu
24gb
low-latency
Instructions to use bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling
- SGLang
How to use bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling 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 "bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling" \ --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": "bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling", "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 "bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling" \ --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": "bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling with Docker Model Runner:
docker model run hf.co/bowmanslayer/Qwen3.6-27B-Text-Only-W4A16-g128-MTP-ToolCalling
Ctrl+K
self/quantization_config.json: relabel for Marlin โ match self/config.json embedded qc (was missed in earlier sync)
60b1ff7 verified