Comments (1)
hiyouga
commented on May 9, 2024
3
如果和 deepspeed 对标的话，我想你指的应该是 accelerate？ peft 和 deepspeed 不是很有可比性。
对于分布式训练，考虑到 huggingface 的 trainer API 原生支持 accelerate，能够大大减少代码量，因而选择了 huggingface 的库。
我们目前没有做过不同框架的技术比较，期待用户的结果反馈。
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Related Issues (20)
- when `per_device_eval_batch_size` > 1 and launch by deepspeed, RuntimeError: Tensors must be contiguous HOT 5
- 请问lora训练是只会训练注意力层，在注意力层加适配器吗？而不训练前馈层。然后freeze是训练前馈层 HOT 1
- lora微调之后导出的完整模型文件应该要如何调用 我使用transformers的接口加载模型报错 HOT 2
- 显存占用问题
- ValueError: Cannot merge LORA layers when the model is loaded in 8-bit mode
- collator.py的第126行与preprocess.py的preprocess_supervised_dataset是不是存在冲突？input_ids拼接了2次labels HOT 2
- 4*V100 32g配置，满足zero3全量微调吗？ HOT 4
- Learning Scheduler Issue HOT 2
- 请问下在4-bit量化模式Lora微调最小的显存要求 HOT 1
- 2400条数据,10个epoch,pre_seq_len=128,lora训练,为什么推理时显示trainable params: 0 || all params: 6243584000 || trainable%: 0.0000,是数据量不够吗,下边贴出训练参数 HOT 1
- 跑sft阶段出现这个问题，环境应该是ok的 HOT 2
- 仓库过大，git下载慢 HOT 2
- 不理解为什么这个模型是paddingleft. 编码之后开始全是一堆-100的token, 感觉很难llm收敛.
- lora_target 的可用值有哪些？ HOT 2
- step和epoch一样 HOT 1
- 用默认参数微调chatglm2之后对话能力大幅度下降 HOT 1
- 数据集oaast_rm_zh问题
- epoch的选择&数据集构造 HOT 1
- CUDA error: an illegal memory access was encountered HOT 1
- 微调后不起效果，是我哪步有问题吗 HOT 1
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