GitHub - cliangyu/Cola: [NeurIPS2023] Official implementation of the paper "Large Language Models are Visual Reasoning Coordinators"
By grounding LLMs with use-case-specific information through RAG, the quality and accuracy of responses are improved.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
multimodal-maestro
👋 hello
Multimodal-Maestro gives you more control over large multimodal models to get the outputs you want. With more effective prompting tactics, you can get multimodal models to do tasks you didn't know (or think!) were possible. Curious how it works? Try our HF space!
👋 hello
Multimodal-Maestro gives you more control over large multimodal models to get the outputs you want. With more effective prompting tactics, you can get multimodal models to do tasks you didn't know (or think!) were possible. Curious how it works? Try our HF space!
roboflow • GitHub - roboflow/multimodal-maestro: Effective prompting for Large Multimodal Models like GPT-4 Vision, LLaVA or CogVLM. 🔥
Jay Alammar – Visualizing machine learning one concept at a time.
jalammar.github.io