Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️
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Updated
May 29, 2024 - Python
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)
CLIP based Zero Shot Instance Segmentation
Using Segment-Anything and CLIP to generate pixel-aligned semantic features.
Searching Images: From Clip And Beyond
Group images by provided labels using OpenAI/CLIP
use SAM and OpenCLIP to perform zero-shot object detection using COCO 2017 val split.
Clipora is a powerful toolkit for fine-tuning OpenCLIP models using Low Rank Adapters (LoRA).
A goal-oriented planning to lift VLN performance for Closed-Loop Navigation: Simple, Yet Effective
Text-to-image search with OpenCLIP, Docker, Flask, Faiss, etc. and a basic front-end.
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