我相信pickle和OpenAI之间存在一个已知的问题(请查看相关问题),但在使用
我相信pickle和OpenAI之间存在一个已知的问题(请查看相关问题),但在使用
Hello, I'm encountering an issue with guided topic modeling on different dataset sizes. With a smaller dataset, the same code and same seed topic list work seamlessly. However, when applied to a larger dataset, it fails. The specific problem I'm facing is: ...
Hierarchical Topic Modeling .hierarchical_topics(docs) Guided Topic Modeling BERTopic(seed_topic_list=seed_topic_list) Zero-shot Topic Modeling BERTopic(zeroshot_topic_list=zeroshot_topic_list) Merge Multiple Models BERTopic.merge_models([topic_model_1, topic_model_2])Visualizations...
3、CoT引导过滤器(CoT-guided Filter) 使用Chain of Thought(CoT)来指导过滤器,精确识别包含关键事实细节的片段,指导LLMs逐步关注相关知识点。 4、LLM增强生成器(LLM-augmented Generator) 结合全局信息和事实细节生成最终答案。 总结 本文主要围绕RAG,介绍了2个工作,一个是RAG与知识图谱结合:全局视角的知识图谱构建...
3、CoT引导过滤器(CoT-guided Filter) 使用Chain of Thought(CoT)来指导过滤器,精确识别包含关键事实细节的片段,指导LLMs逐步关注相关知识点。 4、LLM增强生成器(LLM-augmented Generator) 结合全局信息和事实细节生成最终答案。 总结 本文主要围绕RAG,介绍了2个工作,一个是RAG与知识图谱结合:全局视角的知识图谱构建...
3、CoT引导过滤器(CoT-guided Filter) 使用Chain of Thought(CoT)来指导过滤器,精确识别包含关键事实细节的片段,指导LLMs逐步关注相关知识点。 4、LLM增强生成器(LLM-augmented Generator) 结合全局信息和事实细节生成最终答案。 总结 本文主要围绕RAG,介绍了2个工作,一个是RAG与知识图谱结合:全局视角的知识图谱构建...
Whilst BERTopic is easy to get started with, it supports a range of advanced approaches to topic modelling including guided, supervised, semi-supervised and manual topic modelling. More recently BERTopic has added support for multi-modal topic models. BERTopic also have a rich set of tools for...
3、CoT引导过滤器(CoT-guided Filter) 使用Chain of Thought(CoT)来指导过滤器,精确识别包含关键事实细节的片段,指导LLMs逐步关注相关知识点。 4、LLM增强生成器(LLM-augmented Generator) 结合全局信息和事实细节生成最终答案。 总结 本文主要围绕RAG,介绍了2个工作,一个是RAG与知识图谱结合:全局视角的知识图谱构建...
Having said that, if there is no difference in performance, then you might go for BERTopic as it allows you to perform variations of topic modeling techniques, such as dynamic topic modeling and guided topic modeling which is currently not found in Top2Vec. Top2Vec, in contrast, has featur...