[inference] support sglang backend (#7278)
* Mimic SGLang offline Engine * Add more tests and args * Pass all current tests * Clean Code * fix sample_params * clean code * Fix Stream Chat * change sglang from engine mode to server mode * fix * Fix Review Issues * Use SGLang Built-In Utilities * Fix test SGLang * Some Doc Issue * fix sglang engine * add readme --------- Co-authored-by: Jin Pan <jpan236@wisc.edu> Co-authored-by: hiyouga <hiyouga@buaa.edu.cn>
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@@ -79,8 +79,8 @@ Choose your path:
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- **Advanced algorithms**: [GaLore](https://github.com/jiaweizzhao/GaLore), [BAdam](https://github.com/Ledzy/BAdam), [APOLLO](https://github.com/zhuhanqing/APOLLO), [Adam-mini](https://github.com/zyushun/Adam-mini), DoRA, LongLoRA, LLaMA Pro, Mixture-of-Depths, LoRA+, LoftQ and PiSSA.
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- **Practical tricks**: [FlashAttention-2](https://github.com/Dao-AILab/flash-attention), [Unsloth](https://github.com/unslothai/unsloth), [Liger Kernel](https://github.com/linkedin/Liger-Kernel), RoPE scaling, NEFTune and rsLoRA.
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- **Wide tasks**: Multi-turn dialogue, tool using, image understanding, visual grounding, video recognition, audio understanding, etc.
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- **Experiment monitors**: LlamaBoard, TensorBoard, Wandb, MLflow, SwanLab, etc.
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- **Faster inference**: OpenAI-style API, Gradio UI and CLI with vLLM worker.
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- **Experiment monitors**: LlamaBoard, TensorBoard, Wandb, MLflow, [SwanLab](https://github.com/SwanHubX/SwanLab), etc.
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- **Faster inference**: OpenAI-style API, Gradio UI and CLI with [vLLM worker](https://github.com/vllm-project/vllm) or [SGLang worker](https://github.com/sgl-project/sglang).
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### Day-N Support for Fine-Tuning Cutting-Edge Models
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@@ -106,6 +106,8 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
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## Changelog
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[25/03/15] We supported **[SGLang](https://github.com/sgl-project/sglang)** as inference backend. Try `infer_backend: sglang` to accelerate inference.
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[25/03/12] We supported fine-tuning the **[Gemma-3](https://huggingface.co/blog/gemma3)** model.
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[25/02/24] Announcing **[EasyR1](https://github.com/hiyouga/EasyR1)**, an efficient, scalable and multi-modality RL training framework for efficient GRPO training.
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@@ -437,7 +439,7 @@ cd LLaMA-Factory
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pip install -e ".[torch,metrics]"
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```
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Extra dependencies available: torch, torch-npu, metrics, deepspeed, liger-kernel, bitsandbytes, hqq, eetq, gptq, awq, aqlm, vllm, galore, apollo, badam, adam-mini, qwen, minicpm_v, modelscope, openmind, swanlab, quality
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Extra dependencies available: torch, torch-npu, metrics, deepspeed, liger-kernel, bitsandbytes, hqq, eetq, gptq, awq, aqlm, vllm, sglang, galore, apollo, badam, adam-mini, qwen, minicpm_v, modelscope, openmind, swanlab, quality
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> [!TIP]
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> Use `pip install --no-deps -e .` to resolve package conflicts.
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