参考论文:Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks(2020) RAG(Retrieval-Augmented Generation)技术是一种结合信息检索和生成模型的方法。它通过从外部知识库中检索相关信息,并将这些信息与生成模型结合,以生成更准确和信息丰富的回答。 使用RAG的关键步骤
每个簇中的样本按到簇质心的距离排序,最接近质心的样本首先被选择。 论据生成(Rationale generation):使用 Zero-shot CoT 为选定的问题生成推理链,并构建 Few-shot 提示以运行推理。 三、更多资料 3.1 实用工具 OpenAI Cookbookhas many in-depth examples for how to utilize LLM efficiently. LangChain, a librar...
)#获取压缩后的相关文档compressed_docs = compression_retriever.get_relevant_documents("What is baichuan2 ?")#输出结果fordocincompressed_docs:print(doc) 原来的文档: Baichuan2isa next-generation artificial intelligence model developed by XYZ Corp. Itisdesigned to handle complex natural language processing ...
Code for our paper, "BADGE: BADminton report Generation and Evaluation with LLM," presented at the IJCAI 2024 Workshop IT4PSS. - AndyChiangSH/BADGE
[torch.FloatTensor,torch.FloatTensor,torch.FloatTensor]:"""Compute the Kahneman-Tversky lossfora batchofpolicy and reference model log probabilities.For each batchofn/2chosen examples and n/2rejectedexamples(belonging to n different inputs),calculate the lossasfollows.If generation y~p_chosen,where ...
BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Managem
model=AutoModelForCausalLM.from_pretrained( r"dmayhem93/toolformer_v0_epoch2", torch_dtype=torch.float16, low_cpu_mem_usage=True, ).cuda() generator=pipeline("text-generation", model=model, tokenizer=tokenizer, device=0) calculator_prompt="""Your taskisto add calls to a Calendar API to...
llm-intellij is a plugin for all things LLM. It uses llm-ls as a backend. [!NOTE] When using the Inference API, you will probably encounter some limitations. Subscribe to the PRO plan to avoid getting rate limited in the free tier. https://huggingface.co
(LLM) è un tipo sempre più popolare di intelligenza artificiale progettato per generare risposte scritte di tipo umano alle query. I LLM sono formati su grandi quantità di dati di testo e imparano a prevedere la parola successiva, o sequenza di parole, in base al contesto fornito, ...
Once an LLM has been trained, a base exists on which the AI can be used for practical purposes. By querying the LLM with a prompt, the AI model inference can generate a response, which could be an answer to a question, newly generated text, summarized text or asentiment analysisreport....