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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.
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).
use SAM and OpenCLIP to perform zero-shot object detection using COCO 2017 val split.
Text-to-image search with OpenCLIP, Docker, Flask, Faiss, etc. and a basic front-end.
CLIP based Zero Shot Instance Segmentation
Searching Images: From Clip And Beyond
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.