模型精调(fine-tuning):指通过有监督机器学习的方式,使用标记好的数据库调整微调模型参数,其中指令精调(Instruct tuning)指的是训练数据为特定任务指令和预期模型输出的精调方式,主要使模型能更好的理解和执行指令。 检索增强生成(Retrieval-Augmented Generation,RAG):可以理解为外挂知识库,让模型能获取及时性、专业性...
然而,在大规模预训练模型中,微调(fine-tuning)过程需要针对具体任务生成合适的Instruction指令,这一过程通常需要人工设计和调整,耗时且低效。为了解决这一问题,我们提出了一种面向大模型微调的Instruction指令自动化生成技术——SELF-INSTRUCT,旨在实现大模型微调任务的自动化和高效化。 SELF-INSTRUCT框架主要包括三个部分:...
这个过程可以重复多次迭代,直到完成大量任务。 (In this work, we introduce SELF-INSTRUCT, a semi-automated process for instruction-tuning a pretrained LM using instructional signals from the model itself. The overall process is an iterative bootstrapping algorithm (see Figure 1), which starts off wi...
The process of fine-tuning a base model to obtain an instruct model is called "instruction tuning." 3.2 Dataset The dataset for IFS is derived from a chat dataset, which originally consists of pairs (instruction, response). We will need to model inputs and outputs for models that aren’t...
./scripts/generate_instructions.sh# 2. Identify whether the instruction represents a classification task or not./scripts/is_clf_or_not.sh# 3. Generate instances for each instruction./scripts/generate_instances.sh# 4. Filtering, processing, and reformatting./scripts/prepare_for_finetuning.sh ...
LoRA(Low-Rank Adaptation of Large Language Models)中文含义是大语言模型的低阶适应,是一种PEFT(Parameter-Efficient Fine-Tuning)参数高效微调技术,是微软提出用来解决大语言模型参数微调的技术。其基本原理是冻结预训练好的模型权重参数,在冻结原模型参数的情况下,通过往模型中加入额外的网络层,并只训练这些新增的网...
Seal-Tools: Self-instruct Tool Learning Dataset forAgent Tuning andDetailed Benchmarkdoi:10.1007/978-981-97-9434-8_29This paper presents a new tool learning dataset , which contains tools. Seal-Tools not only offers a large number of tools, but also includes instances which demonstrate the ...
Here is an overview of Self-Instruct: Usage *This work is still in progress. We may update the code and data as we make progress. Please be cautious about the version control. Instruction-tuning using our Self-Instruct data We release a dataset that contains 52k instructions, paired with ...
We also synthesized 62,476 charts, tables, and road map instructions for fine-tuning, verifying the effectiveness of the synthesized data. Leaderboard on Our Abstract Image Benchmark LLMsChartTableRoad MapDashboardRelation GraphFlowchartVisual PuzzlesLayoutAvg. Human 93.5 95.1 75.0 85.3 82.5 65.5 62.5...
LoRA(Low-Rank Adaptation of Large Language Models)中文含义是大语言模型的低阶适应,是一种PEFT(Parameter-Efficient Fine-Tuning)参数高效微调技术,是微软提出用来解决大语言模型参数微调的技术。其基本原理是冻结预训练好的模型权重参数,在冻结原模型参数的情况下,通过往模型中加入额外的网络层,并只训练这些新增的网...