Video-LLaMA
FastChat
Video-LLaMA | FastChat | |
---|---|---|
8 | 83 | |
2,455 | 34,514 | |
5.8% | 4.3% | |
6.6 | 9.6 | |
5 days ago | 6 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
Video-LLaMA
- Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
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OpenAI vs Google, Detect ChatGPT Content with 99% accuracy, Navigating AI compute costs
👀 Video-LLaMA - Empower large language models with video and audio understanding capability. (link) 🦦 Otter - Multi-modal model with improved instruction-following and in-context learning ability. 🔗 Linkly.AI - AI-powered lead analytics and management platform that helps you track, analyze, and streamline your leads in one place. 🎬 Jet Cut Ready - AI plugin for Adobe Premiere Pro that automatically removes silent parts in videos. (link) 💬 HeyGen's ChatGPT Plugin - Convert text into high-quality videos using AI text and video generation.
- Video-LLaMA: Instruction-Tuned Audio-Visual Lang Model for Video Understanding
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Unleash the Power of Video-LLaMA: Revolutionizing Language Models with Video and Audio Understanding!
Prepare to be blown away by the cutting-edge Video-LLaMA project! We're pushing the boundaries of language models by equipping them with the remarkable ability to comprehend video and audio. Get ready for an extraordinary adventure! 🌟
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Video-LLaMA An Instruction-tuned Audio-Visual Language Model for Video Understanding
Source Code: The codebase for pre-training and fine-tuning the Video-LLaMA model as well as the model weights are available on GitHub: https://github.com/DAMO-NLP-SG/Video-LLaMA
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Video-ChatGPT: Redefining Interactions with Visual Data
Tons of cool stuff happening in the space, also recently saw the LLaMa-Video version of this - https://github.com/DAMO-NLP-SG/Video-LLaMA
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Meet Video-LLaMA: A Multi-Modal Framework that Empowers Large Language Models (LLMs) with the Capability of Understanding both Visual and Auditory Content in the Video
Code: https://github.com/DAMO-NLP-SG/Video-LLaMA
FastChat
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GPT4.5 or GPT5 being tested on LMSYS?
gpt2-chatbot isn't the only "mystery model" on LMSYS. Another is "deluxe-chat".
When asked about it in October last year, LMSYS replied [0] "It is an experiment we are running currently. More details will be revealed later"
One distinguishing feature of "deluxe-chat": although it gives high quality answers, it is very slow, so slow that the arena displays a warning whenever it is invoked
[0] https://github.com/lm-sys/FastChat/issues/2527
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LLMs on your local Computer (Part 1)
FastChat
- FLaNK AI for 11 March 2024
- FLaNK 04 March 2024
- ChatGPT for Teams
- FastChat: An open platform for training and serving large language models
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LM Studio – Discover, download, and run local LLMs
How does it compare with something like FastChat? https://github.com/lm-sys/FastChat
Feature set seems like a decent amount of overlap. One limitation of FastChat, as far as I can tell, is that one is limited to the models that FastChat supports (though I think it would be minor to modify it to support arbitrary models?)
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Video-LLaVA
Looks like the Vicuna repo is Apache 2.0 also[1].
What's the interpretation of copyright law that would prevent the code being Apache 2.0 based on the source of the fine-tuning dataset?
[1] https://github.com/lm-sys/FastChat
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
Check how to start with FastChat. Support FastChat on GitHub ⭐
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Show HN: ChatAPI – PWA to Use ChatGPT by API Build with Alpine.js
For something a little heavier but much more robust in terms of features/functionality I've been enjoying FastChat: https://github.com/lm-sys/FastChat
It allows you to plug in different backends so that you can use OpenAI compatible clients with various LLM's, selfhosted or otherwise.