affine-2

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Quick Summary

AI model with specialized capabilities.

Code Examples

Step 2: Launch Model Serverbashvllm
pip install -U vllm \
    --torch-backend=auto \
    --extra-index-url https://wheels.vllm.ai/nightly
bashvllm
VLLM_ATTENTION_BACKEND=DUAL_CHUNK_FLASH_ATTN VLLM_USE_V1=0 \
vllm serve ./Qwen3-235B-A22B-Thinking-2507 \
  --tensor-parallel-size 8 \
  --max-model-len 1010000 \
  --enable-chunked-prefill \
  --max-num-batched-tokens 131072 \
  --enforce-eager \
  --max-num-seqs 1 \
  --gpu-memory-utilization 0.85 \
  --enable-reasoning --reasoning-parser deepseek_r1
Option 2: Using SGLangbash
git clone https://github.com/sgl-project/sglang.git
cd sglang
pip install -e "python[all]"
bash
python3 -m sglang.launch_server \
    --model-path ./Qwen3-235B-A22B-Thinking-2507 \
    --context-length 1010000 \
    --mem-frac 0.75 \
    --attention-backend dual_chunk_flash_attn \
    --tp 8 \
    --chunked-prefill-size 131072 \
    --reasoning-parser deepseek-r1

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