GitHub - kaistAI/CoT-Collection: [Under Review] The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
Deep-ML
deep-ml.com🥤 Cola [NeurIPS 2023]
Large Language Models are Visual Reasoning Coordinators
Liangyu Chen*,†,♥ Bo Li*,♥ Sheng Shen♣ Jingkang Yang♥
Chunyuan Li♠Kurt Keutzer♣ Trevor Darrell♣ Ziwei Liu✉,♥
♥S-Lab, Nanyang Technological University
♣University of California, Berkeley ♠Microsoft Research, Redmond
*Equal Contribution †Project Lead ✉Corresponding Author... See more
Large Language Models are Visual Reasoning Coordinators
Liangyu Chen*,†,♥ Bo Li*,♥ Sheng Shen♣ Jingkang Yang♥
Chunyuan Li♠Kurt Keutzer♣ Trevor Darrell♣ Ziwei Liu✉,♥
♥S-Lab, Nanyang Technological University
♣University of California, Berkeley ♠Microsoft Research, Redmond
*Equal Contribution †Project Lead ✉Corresponding Author... See more
cliangyu • GitHub - cliangyu/Cola: [NeurIPS2023] Official implementation of the paper "Large Language Models are Visual Reasoning Coordinators"
Fine-Tuning for LLM Research by AI Hero
This repo contains the code that will be run inside the container. Alternatively, this code can also be run natively. The container is built and pushed to the repo using Github actions (see below). You can launch the fine tuning job using the examples in the https://github.com/ai-hero/llm-research-examples pr... See more
This repo contains the code that will be run inside the container. Alternatively, this code can also be run natively. The container is built and pushed to the repo using Github actions (see below). You can launch the fine tuning job using the examples in the https://github.com/ai-hero/llm-research-examples pr... See more
GitHub - ai-hero/llm-research-fine-tuning
Welcome to RAGatouille
Easily use and train state of the art retrieval methods in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
The main motivation of RAGatouille is simple: bridging the gap between state-of-the-art research and alchemical RAG pipeline practices. RAG is complex, and there are many moving parts. To g... See more
Easily use and train state of the art retrieval methods in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
The main motivation of RAGatouille is simple: bridging the gap between state-of-the-art research and alchemical RAG pipeline practices. RAG is complex, and there are many moving parts. To g... See more