Fix formatting in long code blocks (#10528)
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@@ -158,7 +158,14 @@ The precompilation process typically takes around 10 minutes to complete.
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**Usage**:
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Add arguments `--speculative-algorithm`, `--speculative-num-steps`, `--speculative-eagle-topk` and `--speculative-num-draft-tokens` to enable this feature. For example:
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```
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python3 -m sglang.launch_server --model-path deepseek-ai/DeepSeek-V3-0324 --speculative-algorithm EAGLE --speculative-num-steps 1 --speculative-eagle-topk 1 --speculative-num-draft-tokens 2 --trust-remote-code --tp 8
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python3 -m sglang.launch_server \
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--model-path deepseek-ai/DeepSeek-V3-0324 \
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--speculative-algorithm EAGLE \
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--speculative-num-steps 1 \
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--speculative-eagle-topk 1 \
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--speculative-num-draft-tokens 2 \
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--trust-remote-code \
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--tp 8
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```
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- The best configuration for `--speculative-num-steps`, `--speculative-eagle-topk` and `--speculative-num-draft-tokens` can be searched with [bench_speculative.py](https://github.com/sgl-project/sglang/blob/main/scripts/playground/bench_speculative.py) script for given batch size. The minimum configuration is `--speculative-num-steps 1 --speculative-eagle-topk 1 --speculative-num-draft-tokens 2`, which can achieve speedup for larger batch sizes.
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- FlashAttention3, FlashMLA, and Triton backend fully supports MTP usage. For FlashInfer backend (`--attention-backend flashinfer`) with speculative decoding,`--speculative-eagle-topk` parameter should be set to `1`. MTP support for the CutlassMLA and TRTLLM MLA backends are still under development.
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@@ -177,7 +184,14 @@ See [Reasoning Parser](https://docs.sglang.ai/advanced_features/separate_reasoni
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Add arguments `--tool-call-parser deepseekv3` and `--chat-template ./examples/chat_template/tool_chat_template_deepseekv3.jinja`(recommended) to enable this feature. For example (running on 1 * H20 node):
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```
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python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3-0324 --tp 8 --port 30000 --host 0.0.0.0 --mem-fraction-static 0.9 --tool-call-parser deepseekv3 --chat-template ./examples/chat_template/tool_chat_template_deepseekv3.jinja
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python3 -m sglang.launch_server \
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--model deepseek-ai/DeepSeek-V3-0324 \
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--tp 8 \
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--port 30000 \
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--host 0.0.0.0 \
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--mem-fraction-static 0.9 \
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--tool-call-parser deepseekv3 \
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--chat-template ./examples/chat_template/tool_chat_template_deepseekv3.jinja
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```
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Sample Request:
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