LAVIS
FastChat
| LAVIS | FastChat | |
|---|---|---|
| 18 | 83 | |
| 8,781 | 34,277 | |
| 2.9% | 3.6% | |
| 6.3 | 9.6 | |
| 19 days ago | 4 days ago | |
| Jupyter Notebook | 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.
LAVIS
- FLaNK AI for 11 March 2024
- FLaNK 04 March 2024
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[D] Why is most Open Source AI happening outside the USA?
For multimodal, there's China (*many), then Salesforce.
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Need help for a colab notebook running Lavis blip2_instruct_vicuna13b?
Been trying for all day to get a working inference for this example: https://github.com/salesforce/LAVIS/tree/main/projects/instructblip
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most sane web3 job listing
There's also been big breakthroughs in computer vision. Not that long ago it was hard to recognize if a photo contained a bird; that's solved now by models like CLIP, Yolo, or Segment Anything. Now research has moved on to generating 3D scenes from images or interactively answering questions about images.
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I work at a non-tech company and have been asked to make software that is impossible. How do I explain it to my boss?
The new hotness is multimodal vision-language models like InstructBLIP that can interactively answer questions about images. Check out the examples in the github repo, I would not have thought this was possible a few years ago.
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Two-minute Daily AI Update (Date: 5/15/2023)
Salesforce’s BLIP family has a new member– InstructBLIP, a vision-language instruction-tuning framework using BLIP-2 models. It has achieved state-of-the-art zero-shot generalization performance on a wide range of vision-language tasks, substantially outperforming BLIP-2 and Flamingo. (Source)
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InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Github
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Can I use my own art as a training set?
Most of my workflows are self-made. For captioning I used Blip-2 in a custom script I made that automates the process by going into directories and their sub-directories and creates a .txt file beside each image. This way I can keep my images organized in their proper directories, without having to put dump them all in a single place.
- FLiP Stack Weekly for 13-Feb-2023
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.
What are some alternatives?
pytorch-widedeep - A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
CLIP-Caption-Reward - PyTorch code for "Fine-grained Image Captioning with CLIP Reward" (Findings of NAACL 2022)
llama.cpp - LLM inference in C/C++
sparseml - Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
gpt4all - gpt4all: run open-source LLMs anywhere
robo-vln - Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.
DeepViewAgg - [CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
linkis - Apache Linkis builds a computation middleware layer to facilitate connection, governance and orchestration between the upper applications and the underlying data engines.
llama-cpp-python - Python bindings for llama.cpp