Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️

Reproducible scaling laws for contrastive language-image learning (https://arxiv.org/abs/2212.07143)

Using Segment-Anything and CLIP to generate pixel-aligned semantic features.

[Official] [IROS 2024] A goal-oriented planning to lift VLN performance for Closed-Loop Navigation: Simple, Yet Effective

Clipora is a powerful toolkit for fine-tuning OpenCLIP models using Low Rank Adapters (LoRA).

Text-to-image search with OpenCLIP, Docker, Flask, Faiss, etc. and a basic front-end.

use SAM and OpenCLIP to perform zero-shot object detection using COCO 2017 val split.

A simple open-sourced SigLIP model finetuned on Genshin Impact's image-text pairs.

Group images by provided labels using OpenAI/CLIP

Searching Images: From Clip And Beyond

CLIP based Zero Shot Instance Segmentation

A quick test using Supabase to test if pgvector is the right solution for a different project. The embedding model I will be using OpenAI's Clip Model which will allow me to embed images and text in the same vector space.

Using Docker compose to start up Triton with the OpenClip model, to encode text in to vectors

This project offers an API for vectorizing images using OpenAI's CLIP model via BentoML and integrates Milvus for efficient vector storage and search

Android Studio plugin for fuzzy and AI-driven drawable search

Deploy BentoML to ECS on AWS using Terraform to create vectors quickly and easily.