Update to v0.9.3

README_en.md

@@ -105,7 +105,6 @@ Choose your path:
 
 ## Blogs
 
-- [A One-Stop Code-Free Model Reinforcement Learning and Deployment Platform based on LLaMA-Factory and EasyR1](https://aws.amazon.com/cn/blogs/china/building-llm-model-hub-based-on-llamafactory-and-easyr1/) (Chinese)
 - [Fine-tune Qwen2.5-VL for Autonomous Driving using LLaMA-Factory](https://docs.alayanew.com/docs/documents/useGuide/LLaMAFactory/mutiple/?utm_source=LLaMA-Factory) (Chinese)
 - [How Apoidea Group enhances visual information extraction from banking documents with multimodal models using LLaMA-Factory on Amazon SageMaker HyperPod](https://aws.amazon.com/cn/blogs/machine-learning/how-apoidea-group-enhances-visual-information-extraction-from-banking-documents-with-multimodal-models-using-llama-factory-on-amazon-sagemaker-hyperpod/) (English)
 - [Easy Dataset × LLaMA Factory: Enabling LLMs to Efficiently Learn Domain Knowledge](https://buaa-act.feishu.cn/wiki/GVzlwYcRFiR8OLkHbL6cQpYin7g) (English)

README_zh.md

@@ -107,7 +107,6 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
 
 ## 官方博客
 
-- [基于 LLaMA-Factory 和 EasyR1 打造一站式无代码大模型强化学习和部署平台 LLM Model Hub](https://aws.amazon.com/cn/blogs/china/building-llm-model-hub-based-on-llamafactory-and-easyr1/)（中文）
 - [使用 LLaMA-Factory 微调 Qwen2.5-VL 实现自动驾驶场景微调](https://docs.alayanew.com/docs/documents/useGuide/LLaMAFactory/mutiple/?utm_source=LLaMA-Factory)（中文）
 - [通过亚马逊 SageMaker HyperPod 上的 LLaMA-Factory 增强多模态模型银行文档的视觉信息提取](https://aws.amazon.com/cn/blogs/machine-learning/how-apoidea-group-enhances-visual-information-extraction-from-banking-documents-with-multimodal-models-using-llama-factory-on-amazon-sagemaker-hyperpod/)（英文）
 - [Easy Dataset × LLaMA Factory: 让大模型高效学习领域知识](https://buaa-act.feishu.cn/wiki/KY9xwTGs1iqHrRkjXBwcZP9WnL9)（中文）

setup.py

@@ -52,7 +52,7 @@ extra_require = {
     "eetq": ["eetq"],
     "gptq": ["optimum>=1.24.0", "gptqmodel>=2.0.0"],
     "aqlm": ["aqlm[gpu]>=1.1.0"],
-    "vllm": ["vllm>=0.4.3,<=0.9.1"],
+    "vllm": ["vllm>=0.4.3,<=0.8.6"],
     "sglang": ["sglang[srt]>=0.4.5", "transformers==4.51.1"],
     "galore": ["galore-torch"],
     "apollo": ["apollo-torch"],

src/llamafactory/extras/env.py

@@ -27,7 +27,7 @@ import trl
 from transformers.utils import is_torch_cuda_available, is_torch_npu_available
 
 
-VERSION = "0.9.4.dev0"
+VERSION = "0.9.3"
 
 
 def print_env() -> None:

src/llamafactory/hparams/parser.py

@@ -148,7 +148,7 @@ def _check_extra_dependencies(
         check_version("mixture-of-depth>=1.1.6", mandatory=True)
 
     if model_args.infer_backend == EngineName.VLLM:
-        check_version("vllm>=0.4.3,<=0.9.1")
+        check_version("vllm>=0.4.3,<=0.8.6")
         check_version("vllm", mandatory=True)
     elif model_args.infer_backend == EngineName.SGLANG:
         check_version("sglang>=0.4.5")