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Related Issues (20)
- How to avoid using bf16 due to a old but fixed coda, for dpo and sft.
- llama3.1 70B OOM for qlora+fsdp sft. HOT 1
- Qwen2-72B-Instruct-GPTQ-Int4量化模型Lora微调后,无法合并导出模型-Cannot merge adapters to a quantized model.
- 利用 vLLM 部署 OpenAI API是否可以支持vllm的LoRA Adapters
- 运行qwen-1.5-72B报错 HOT 1
- 预训练效率极低 HOT 1
- Lora SFT过程和Inference过程中设定的eval_dataset相同,为什么两者的evla_runtime相差特别多(Inference过程中需要的时间更久 HOT 1
- ...
- 使用命令行推理时,怎样设置 share=True ? HOT 2
- glm4-9b-chat predict和推理报错 HOT 1
- sft训练为什么要拼接label呢
- help: padding token
- simpo unexpected gibberish output on inference
- 【Help】增量预训练后执行推理predict,"stage": "sft", "do_predict": true,也要选为sft吗 HOT 1
- 请问一下后续有支持DCLM-7B微调的计划吗
- 多卡并行训练下,还是内存溢出,并不生效 HOT 1
- 使用LLaMAFactory lora微调后得到适配器权重,使用llamafactory-cli export 后的模型权重,与用peft merge_and_unload()的权重不一致
- A100(80G)*4 lora微调Qwen2-72B-Instruct模型,显存溢出 HOT 1
- LLaMA Factory, version 0.8.4.dev0 on Ascend910B failed for missing Op OnesLike
- 能不能把可选的依赖也直接放在包里呢
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