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incoai
/
Qwen3.8-27B-DFlash2

Text Generation
Transformers
Safetensors
qwen3
dflash2
speculative-decoding
block-diffusion
draft-model
sglang
vllm
text-generation-inference
Model card Files Files and versions
xet
Community
12

Instructions to use incoai/Qwen3.8-27B-DFlash2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use incoai/Qwen3.8-27B-DFlash2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="incoai/Qwen3.8-27B-DFlash2")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("incoai/Qwen3.8-27B-DFlash2")
    model = AutoModel.from_pretrained("incoai/Qwen3.8-27B-DFlash2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use incoai/Qwen3.8-27B-DFlash2 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "incoai/Qwen3.8-27B-DFlash2"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "incoai/Qwen3.8-27B-DFlash2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/incoai/Qwen3.8-27B-DFlash2
  • SGLang

    How to use incoai/Qwen3.8-27B-DFlash2 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 "incoai/Qwen3.8-27B-DFlash2" \
        --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": "incoai/Qwen3.8-27B-DFlash2",
    		"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 "incoai/Qwen3.8-27B-DFlash2" \
            --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": "incoai/Qwen3.8-27B-DFlash2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use incoai/Qwen3.8-27B-DFlash2 with Docker Model Runner:

    docker model run hf.co/incoai/Qwen3.8-27B-DFlash2
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Request: a DFlash2 helper for BAAI/AREX-2

➕ 1
#12 opened about 1 month ago by
muscleotter

vLLM + hybrid Qwen3.8 target: prefix-cache hits return garbage (fixed by vLLM PR 55601), reuse lags a turn, and notes for >262K

❤️ 1
#11 opened about 1 month ago by
amittell

Resolved

#10 opened 2 months ago by
sekiropuddin

Shall I reduce the num of spec tokens?

2
#9 opened 2 months ago by
Nunodonato

Extended context with Qwen3.8-27B-DFlash2

#8 opened 2 months ago by
GizzmoShifu

When will it come to mainline vLLM Git?

#7 opened 2 months ago by
pathosethoslogos

Some realworld testing

#6 opened 3 months ago by
Izenflamm

Made Sglang + Dflash2 + Docker

#5 opened 3 months ago by
AIReach

Can the Qwen3.5-4B model be released?

👀 1
#4 opened 3 months ago by
liqianhao112

Slowdown on M1 Max (32GB)

#3 opened 3 months ago by
brechtm

FP8

2
#2 opened 3 months ago by
vcerny
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