Overview of our two-stage fine-tuning strategy. We run prompt
Unlocking the Potential of Prompt Flow: An Illustrative Example of
Retrieval Augmented Generation (RAG) for LLMs
EI-CLIP Entity-aware Interventional Contrastive Learning for E-commerce Cross-mo_哔哩哔哩_bilibili
Fine-Tune a Model - SageMaker
A Beginner's Guide to Fine-Tuning Mixtral Instruct Model, by Adithya S K
Applied Sciences, Free Full-Text
The LLM Triad: Tune, Prompt, Reward - Gradient Flow
The architecture of today's LLM applications - The GitHub Blog
DINO-GPT4-V: Use GPT-4V in a Two-Stage Detection Model
Cho-Jui HSIEH, University of Texas at Austin, TX, UT, Department of Computer Science
Cho-Jui HSIEH, University of Texas at Austin, TX, UT, Department of Computer Science