Modify readme and codes

README.md

@@ -62,18 +62,17 @@ vllm: 0.6.2+das.opt3.dtk2504
 git clone https://developer.sourcefind.cn/codes/OpenDAS/llama-factory
 ```
 
-2. 通过[预训练权重](#预训练权重)下载预训练模型，当前用例使用[Meta-Llama-3-8B-Instruct](http://113.200.138.88:18080/aimodels/Meta-Llama-3-8B-Instruct)模型。
+2. 通过[预训练权重](#预训练权重)下载预训练模型，当前用例使用[Llama-4-Scout-17B-16E-Instruct](https://www.scnet.cn/ui/aihub/models/openaimodels/Llama-4-Scout-17B-16E-Instruct)模型。
 
 #### 全参微调
 
 SFT训练脚本示例，参考`llama-factory/train_full`下对应yaml文件。
 
 **参数修改**：
---model_name_or_path 修改为待训练模型地址，如 /data/Meta-llama3-models/Meta-Llama-3-8B-Instruct
---dataset 微调训练集名称，可选数据集请参考/LLaMA-Factory-0.6.3/data/dataset_info.json
---template 将 default 修改为 llama3
+--model_name_or_path 修改为待训练模型地址，如 `/data/Llama-4-Scout-17B-16E-Instruct`
+--dataset 微调训练集名称，可选数据集请参考 `llama-factory/data/dataset_info.json`
+--template 将 default 修改为 `llama4`
 --output_dir 模型保存地址
---fp16 或 --bf16 开启混合精度，单精度可使用 --pure_bf16
 其他参数如：--learning_rate、--save_steps可根据自身硬件及需求进行修改。
 
 #### lora微调
@@ -133,37 +132,15 @@ python infer_transformers.py --model_id /path_of/model_id
 制造,广媒,家居,教育
 
 ## 预训练权重
-
-
-模型目录结构如下：
-```bash
-├── model_save_path
-│   ├── Meta-Llama-3-8B
-│       ├── original
-│           ├── consolidated.00.pth
-│           ├── params.json
-│           └── tokenizer.model
-│       ├── config.json
-│       ├── configuration.json
-│       ├── generation_config.json
-│       ├── LICENSE
-│       ├── model-00001-of-00004.safetensors
-│       ├── model-00002-of-00004.safetensors
-│       ├── model-00003-of-00004.safetensors
-│       ├── model-00004-of-00004.safetensors
-│       ├── model.safetensors.index.json
-│       ├── README.md
-│       ├── special_tokens_map.json
-│       ├── tokenizer_config.json
-│       ├── tokenizer.json
-│       └── USE_POLICY.md
-```
+通过[SCNet AI社区模型库](https://www.scnet.cn/ui/aihub/models)下载预训练模型:
+- [Llama-4-Scout-17B-16E](https://www.scnet.cn/ui/aihub/models/openaimodels/Llama-4-Scout-17B-16E)
+- [Llama-4-Scout-17B-16E-Instruct](https://www.scnet.cn/ui/aihub/models/openaimodels/Llama-4-Scout-17B-16E-Instruct)
+- [Llama-4-Maverick-17B-128E](https://www.scnet.cn/ui/aihub/models/openaimodels/Llama-4-Maverick-17B-128E)
+- [Llama-4-Maverick-17B-128E-Instruct](https://www.scnet.cn/ui/aihub/models/openaimodels/Llama-4-Maverick-17B-128E-Instruct)
 
 ## 源码仓库及问题反馈
 - https://developer.hpccube.com/codes/modelzoo/llama4_pytorch
 
 ## 参考资料
-- https://github.com/meta-llama/llama3
-- https://github.com/InternLM/xtuner
-- https://github.com/meta-llama/llama-recipes
-- https://github.com/hiyouga/LLaMA-Factory/tree/v0.6.3
+- https://github.com/meta-llama/llama-models/tree/main/models/llama4
+- https://github.com/hiyouga/LLaMA-Factory/

infer_transformers.py

@@ -22,9 +22,8 @@ if __name__ == "__main__":
         device_map="auto",
         torch_dtype=torch.bfloat16,
     )
-
-    url1 = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/0052a70beed5bf71b92610a43a52df6d286cd5f3/diffusers/rabbit.jpg"
-    url2 = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/datasets/cat_style_layout.png"
+    url1 = "datasets/rabbit.jpg"
+    url2 = "datasets/cat_style_layout.png"
     messages = [
         {
             "role": "user",