上一篇里面我们聊到了Zero shot prompts,它对于一些极其复杂或者完全没有见到过的领域问题无能为力。这一篇里我们可以尝试使用few shot技术使用少量(通常是10个以内)的样本,对模型进行训练来执行特定的任务。当我们的数据样本较少或者需要极高代价来获取数据的时候,使用few shot是个不错的选择。 Few-shot propmts通过在
它使用嵌入模型来计算输入与少量示例之间的语义相似度,并使用向量存储来执行最近邻搜索。 fromlangchain.promptsimportPromptTemplatefromlangchain.promptsimportFewShotPromptTemplatefromlangchain.prompts.example_selectorimportSemanticSimilarityExampleSelectorfromlangchain_community.vectorstoresimportFAISS, Chromafromlangchain...
fromlangchain.prompts.few_shotimportFewShotPromptTemplatefromlangchain.prompts.promptimportPromptTemplateexamples=[{"question":"穆罕默德·阿里和艾伦·图灵谁活得更久?","answer":"""这里需要追问吗:是的。追问:穆罕默德·阿里去世时多大?中间答案:穆罕默德·阿里去世时74岁。追问:艾伦·图灵去世时多大?中间答案:...
One challenge of using few-shot prompts is that as the number of examples increases, the prompt can become excessively large, leading to inefficiencies and potential performance issues. To address this, a dynamic few-shot prompt technique can be employed. In this approach, a comprehensive l...
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Kai: Because Generative AI can really boost your productivity if used correctly, and knowing how to write prompts correctly is the key to helping you use generative AIs. Student: What will I learn from this tutorial? Kai: This tutorial gives step-by-step guides on how to write AI prompts ...
The answers to “What is the difference between zero-shot and few-shot prompts?” would also point to the element of control. In zero-shot prompting, the model relies on pre-trained knowledge, thereby reducing control over the output. On the other hand, few-shot prompting can help in refi...
Limited Context: Few-shot prompts may not provide enough context for complex tasks, leading to potential inaccuracies in responses. Fine-tuning Challenges: Training models for few-shot learning can be complex and time-consuming, especially for custom or domain-specific tasks. ...
prompt 的影响因素 Motivation Prompt 中 Example 的排列顺序对模型性能有较大影响(即使已经校准参见好的情况下,选取不同的排列顺序依然会有很大的方差): 校准可以大幅度提高准确率,但是不同的排列顺序方差依然很大 Analysis 提出探测集(probing set),流
few-shot taskmachine reading comprehensionThe article explores various methods for generating questions (prompts) in question-answer approaches to named entity recognition. In such methods, recognition is understood as answering questions about named entities. The system must return valid named entities of...