Merge 38028f4811 into f659b55761

README.md

@@ -219,7 +219,7 @@ minimind2系列旧模型均经过权重映射+（微调训练）QKVO线性层校
 * GPU: NVIDIA GeForce RTX 3090 (24GB) * 8
 * Ubuntu==20.04
 * CUDA==12.2
-* Python==3.10.16
+* Python==3.10.16（实测 3.10 ~ 3.12 均可正常使用）
 * [requirements.txt](./requirements.txt)
 
 </details>
@@ -230,6 +230,7 @@ minimind2系列旧模型均经过权重映射+（微调训练）QKVO线性层校
 # 克隆仓库、安装依赖
 git clone --depth 1 https://github.com/jingyaogong/minimind
 cd minimind && pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple
+# 或使用 uv：uv sync（会自动创建 .venv 并安装 pyproject.toml 中的依赖）
 ```
 
 ## Ⅰ 🚀 模型推理

pyproject.toml

@@ -0,0 +1,44 @@
+[project]
+name = "minimind"
+version = "3.0.0"
+description = "MiniMind: 从0训练极小参数量的中文大语言模型"
+readme = "README.md"
+requires-python = ">=3.10,<3.13"
+# 与 requirements.txt 保持一致；torch 默认走 PyPI（Linux 为 CUDA 版，macOS 为 MPS 版），
+# 如需指定 CUDA 版本可改用 https://download.pytorch.org/whl/ 对应索引
+dependencies = [
+    "datasets==3.6.0",
+    "datasketch==1.6.4",
+    "einops==0.8.1",
+    "fastapi==0.120.1",
+    "flask==3.0.3",
+    "flask-cors==4.0.0",
+    "jieba==0.42.1",
+    "jinja2==3.1.2",
+    "jsonlines==4.0.0",
+    "marshmallow==3.22.0",
+    "modelscope==1.37.0",
+    "ngrok==1.4.0",
+    "nltk==3.8",
+    "numpy==1.26.4",
+    "openai==1.59.6",
+    "protobuf==6.33.5",
+    "psutil==5.9.8",
+    "pydantic==2.11.5",
+    "rich==13.7.1",
+    "scikit-learn==1.5.1",
+    "sentence-transformers==2.3.1",
+    "sentencepiece==0.2.0",
+    "simhash==2.1.2",
+    "streamlit==1.50.0",
+    "swanlab==0.9.8",
+    "tiktoken==0.10.0",
+    "torch==2.6.0",
+    "transformers==4.57.6",
+    "trl==0.13.0",
+    "uvicorn==0.38.0",
+    "wandb==0.22.3",
+]
+
+[tool.uv]
+package = false

requirements.txt

@@ -22,7 +22,6 @@ transformers==4.57.6
 jinja2==3.1.2
 jsonlines==4.0.0
 trl==0.13.0
-ujson==5.1.0
 wandb==0.22.3
 streamlit==1.50.0
 einops==0.8.1