Jintao

leetcode 2038题, segment Tree的模板

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你好, 正在阅读leetcode-cookbook, 写的很好, 遇到了一些问题 1. 关于2038题 As += Acont - 2 Bs += Bcont - 2 是否应该改成 As += 1 Bs += 1 (虽然这两种情况都是通过的, 但这应该是测试样例少的关系) ========= 2. 关于Segment Tree的模板 lazy节点的update,...

deepseek-vl系列的微调支持 (finetune)

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ms-swift大模型训练框架已经支持了deepseek-vl系列模型的推理和微调～ 最佳实践可以查看这里: https://github.com/modelscope/swift/blob/main/docs/source/Multi-Modal/deepseek-vl%E6%9C%80%E4%BD%B3%E5%AE%9E%E8%B7%B5.md

# PR type - [ ] Bug Fix - [x] New Feature - [ ] Document Updates - [ ] More Models or Datasets Support

mPLUG-Owl仓库本身已经提供了非常优秀的微调脚本: [https://github.com/X-PLUG/mPLUG-Owl/tree/main/mPLUG-Owl2/scripts](https://github.com/X-PLUG/mPLUG-Owl/tree/main/mPLUG-Owl2/scripts). ms-swift多模态大模型微调框架集成了mPLUG-Owl2和mPLUG-Owl2.1的推理与微调, 并书写了最佳实践: [https://github.com/modelscope/swift/blob/main/docs/source/Multi-Modal/mplug-owl2%E6%9C%80%E4%BD%B3%E5%AE%9E%E8%B7%B5.md](https://github.com/modelscope/swift/blob/main/docs/source/Multi-Modal/mplug-owl2%E6%9C%80%E4%BD%B3%E5%AE%9E%E8%B7%B5.md) 如果有感兴趣的小伙伴, 可以来使用😊 The mPLUG-Owl2 repository itself provides excellent fine-tuning scripts: [https://github.com/X-PLUG/mPLUG-Owl/tree/main/mPLUG-Owl2/scripts](https://github.com/X-PLUG/mPLUG-Owl/tree/main/mPLUG-Owl2/scripts). The ms-swift multimodal large model fine-tuning framework integrates the inference and fine-tuning of mPLUG-Owl2...

大模型微调框架swift已经支持啦minicpm-v的微调. 😊 最佳实践可以查看这里：https://github.com/modelscope/swift/blob/main/docs/source/Multi-Modal/minicpm-v%E6%9C%80%E4%BD%B3%E5%AE%9E%E8%B7%B5.md

# PR type - [ ] Bug Fix - [ ] New Feature - [ ] Document Updates - [ ] More Models or Datasets Support

**Describe the bug** Model.from_pretraind中处理requirements.txt的bug **To Reproduce** 复现代码： ```python import os os.environ['CUDA_VISIBLE_DEVICES'] = '0,1' from modelscope import Model import torch model = Model.from_pretrained( 'baichuan-inc/Baichuan-13B-Chat', revision='v1.0.8', torch_dtype=torch.float16, device_map='auto') ``` 测试环境：(所有库都是最新的) python==3.10.12 modelscope==1.8.4...