Comments (2)
你模型用的不对,用chat的模型
from llama2-chinese.
可是我用的就是chat的,并且在xinference还可以进行多轮对话
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Related Issues (20)
- 中文乱码 HOT 1
- AttributeError: 'LlamaForCausalLM' object has no attribute 'chat' HOT 2
- 微调过程
- 关于atom-7b-chat微调LORA,Attention mask should be of size (1, 1, 104, 208), but is torch.Size([1, 1, 104, 104]),不知道怎么解决 HOT 1
- 使用vllm优化llama HOT 1
- 如何设置系统提词? HOT 1
- 如何拿到微调后的embedding向量呢 HOT 1
- Docker训练,出现异常
- pretrain的数据为啥用的是sft的数据。 HOT 1
- 微调的输出目录,所输出微调记录内容有问题。 HOT 1
- 70B模型sft和lora需要多大显存和内存 HOT 1
- git clone Llama2-Chinese-13b时报错 HOT 1
- 微调的训练数据怎么准备? HOT 2
- 预训练和全量参数微调该如何选择?
- 微调后"vocab_size": 32001 HOT 1
- AttributeError: 'NoneType' object has no attribute 'to' HOT 1
- https://llama.family/chat#/ 选择 Atom-7B 是否使用 https://huggingface.co/FlagAlpha/Llama2-Chinese-7b-Chat/模型 HOT 3
- 微调过程中学习率的问题
- Atom-7B-32K模型是不是有问题?
- ValueError: We were not able to get the tokenizer using `AutoTokenizer.from_pretrained` with the string that you have passed /data/mlops/Qwen-7B-Chat. If you have a custom tokenizer, you can pass it as input. For now, we only support quantization for text model. Support for vision, speech and multimodel will come later.
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