GPT-4生成的序列往往比GPT-3.5长。Alpaca数据集中的GPT-3.5数据呈现出比我们生成的GPT-4输出分布更长的尾巴,可能是因为Alpaca数据集涉及迭代数据收集过程,在每次迭代中删除类似的指令实例,而这在我们的当前一次性数据生成中不存在。尽管有这个简单的过程,但GPT-4生成的指令-following数据表现出更有利的对齐性能,如后...
Project Page: https://instruction-tuning-with-gpt-4.github.io/ Download BibTex Prior work has shown that finetuning large language models (LLMs) using machine-generated instruction-following data enables such models to achieve remarkable zero-shot capabilities on new tasks, and no human-written ...
Instruction Tuning with GPT-4 Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, Jianfeng Gao MSR-TR-2023-35 |April 2023 Published by Microsoft Project Page: https://instruction-tuning-with-gpt-4.github.io/ Prior work has shown that finetuning large language models (LLMs) using machine...
【Instruction Tuning with GPT-4:GPT-4-LLM是用于指令追踪的模型,通过GPT-4生成数据,用于训练遵循指令的LLM,数据包括使用Alpaca提示生成的英文指令追踪数据、使用ChatGPT将Alpaca提示翻译为中文生成的中文指令追踪数据、用于训练奖励模型的GPT-4排序数据以及用于量化GPT-4和指令追踪模型之间差距的非自然指令数据】'Instruc...
使用GPT-4进行视觉指令学习!Visual Instruction Tuningwith GPT-4 ! Generated by GLIGEN (https://gligen.github.io/): A cute lava llama and glasses 我们分享了LLaVA (Language-and-Vision Assistant),一款展示了某些近似多模态GPT-4水平能力的语言和视觉助手。
Instruction-Tuning-with-GPT-4.github.ioInstruction-Tuning-with-GPT-4.github.ioPublic HTML17 0 contributions in the last year No contributions on September 10th.No contributions on September 17th.No contributions on September 24th.No contributions on October 1st.No contributions on October 8th.No con...
LLaVA: Visual Instruction Tuning with GPT-4 LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day Otter: A Multi-Modal Model with In-Context Instruction Tuning This repo benefits fromLLaMA,Alpaca, andVicuna. Thanks for their wonderful works....
[CL]《Instruction Tuning with GPT-4》B Peng, C Li, P He, M Galley, J Gao [Microsoft Research] (2023) http://t.cn/A6NLSaF5 #机器学习##人工智能##论文#
Instruction Tuning是指通过微调模型来理解并遵循特定的指令或指导,从而提高模型的表现。在最近的研究中,Flan、T0、InstructGPT和TKInstruct等模型在Instruction Tuning方面取得了显著的进步。这些模型通过改进微调方法、引入新的指导策略和优化训练过程等方式,提高了模型对指令的理解和遵循能力。首先,我们来看看Flan模型。
Visual Instruction Tuning:https://zhuanlan.zhihu.com/p/624071363 参考文献 [34] Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, and Jianfeng Gao. Instruction tuning with GPT-4. [43] Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, ...