⚡反应提示 反应提示恰似敏捷的闪电侠,能够迅速对问题作出反应并给出合理答案。#大模型 #深度学习(Deep Learning) #Prompt learning +4 发布于 2024-10-26 22:43・IP 属地上海 赞同37 分享收藏 写下你的评论... 2 条评论 默认 最新 乐一下蒜了 机器学习,未来很会成
Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - feat: add support for lora inline prompt references (#2323) · metercai/SimpleSDXL@3bae73e
一、示例或者案例几个月前,开发 NL2SQL 场景。在 Prompt 中添加了表的结构、场景描述,然后再追加场景案例,最后提交大模型,让大模型输出图数据库对应的 SQL。 接下来给一个 Prompt 例子:模拟 NL2SQL 场景。 学生成绩的结构通过输入中文,产生 SQL在阅读整个 Prompt 之前,先对这份 Prompt 做简单的说明。
The type of prompt template. String toString() Returns a string representation of this object. PromptFlowNodeInlineConfiguration withInferenceConfiguration(PromptInferenceConfiguration inferenceConfiguration) Contains inference configurations for the prompt. PromptFlowNodeInlineConfigurat...
The utility model relates to a body-building device skating, in particular to an inline skating with the braking prompt function, comprising an inline pedestal which is connected with a housing, and the housing is internally provided with shoes or shoe inner sleeves; a plurality of rolling ...
Check for existing issues Completed Describe the bug / provide steps to reproduce it During SSH connections to remote machines, file contents are being displayed inline with the prompt rather than having the prompt appear on its own new ...
Contains configurations for a prompt defined inline in the node. Contents modelId The unique identifier of the model or inference profile to run inference with. Type: String Length Constraints: Minimum length of 1. Maximum length of 2048. Pattern: ^(arn:aws(-[^:]{1,12})?:(bedrock|sage...
The first thing we can do is be more specific with our prompt. Instead of just asking "What is the intent of this request?", we can provide the AI with a list of intents to choose from. This will make the prompt more predictable since the AI will only be able t...
2. 如何评估prompt好坏?如何优化prompt? 3. LLM的偏见问题有遇到过吗?如何解决? 4. vLLM用过吗?PagedAttention 5. 解释一下LoRA,AdaLora,如何初始化矩阵? 6. PPO实现细节,核心思想,损失函数 7. deepseek的GRPO,和PPO的区别? 8. 多模态大模型的了解,用过什么视觉编码器?
5⃣Prompt-Tuning ✅ LoRA: LoRA是一种适用于大模型微调的低秩逼近方法。它通过在预训练模型的层间添加低秩矩阵来引入新参数,这些矩阵可以捕捉任务相关的信息而不会对原始模型参数造成显著影响。LoRA方法的优势在于其能够有效地减少微调过程中所需的额外计算资源和存储需求,同时保持模型的性能。