MiniGPT-4
Auto-GPT
| MiniGPT-4 | Auto-GPT | |
|---|---|---|
| 37 | 1 | |
| 24,899 | 149,910 | |
| 0.8% | - | |
| 9.1 | 10.0 | |
| 13 days ago | 7 months ago | |
| Python | JavaScript | |
| BSD 3-clause "New" or "Revised" License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
MiniGPT-4
-
"Building Machines That Learn and Think Like People", 7 Years Later
I just think the tech has been out for so long it's not as big of a deal. Mini-Gpt4 has been out for 6 months! Of course the descriptions aren't exactly gpt-4 grade, but with mistral 7b being used as the language model instead of llama 7b, the reasoning ability will improve noticeably.
[1] https://github.com/Vision-CAIR/MiniGPT-4
- Minigpt4 Inference on CPU
-
Multimodal LLM for infographics images
Isn't there only two open multimodal LLMs, LLaVA and mini-gpt4?
-
Ai trained on photos
For LLM visual instruction, you can use LLaVA, LaVIN, or MiniGPT-4.
- CLIP and DeepDanbooru Alternatives For Prompt Generation [Relevant Self-Promotion]
-
Looking for a pre trained food recognition model
Please read the rules before posting. If you want a model for visual instruction, use LLaVA, LaVIN, or MiniGPT-4.
- Minigpt-4 (Vicuna 13B + images)
-
Upload a photo of your meal and get roasted by ChatGPT
So we use MiniGPT-4 for image parsing, and yep it does return a pretty detailed (albeit not always accurate) description of the photo. You can actually play around with it on Huggingface here.
We use MiniGPT-4 first to interpret the image and then pass the results onto GPT-4. Hopefully, once GPT-4 makes its multi-modal functionality available, we can do it all in one request.
-
Give some love to multi modal models trained on censored llama based models
But I would like to bring up that there are some multi models(llava, miniGPT-4) that are built based on censored llama based models like vicuna. I tried several multi modal models like llava, minigpt4 and blip2. Llava has very good captioning and question answering abilities and it is also much faster than the others(basically real time), though it has some hallucination issue.
Auto-GPT
-
Overview: AI Assembly Architectures
Auto-GPT: github.com/Significant-Gravitas/Auto-GPT
What are some alternatives?
LLaVA - [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
llama.cpp - LLM inference in C/C++
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
stable-diffusion-webui-wd14-tagger - Labeling extension for Automatic1111's Web UI
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
BooruDatasetTagManager
langchain - 🦜🔗 Build context-aware reasoning applications
bark - 🔊 Text-Prompted Generative Audio Model
JARVIS - JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf