Llama 3.2 11B Vision Radiology Mini

A large-scale vision-language pretrained model based on the Vision Transformer architecture, supporting cross-modal understanding between images and text

FashionCLIP is a vision-language model fine-tuned specifically for the fashion domain based on CLIP, capable of generating universal product representations.

Gemma 3 is a lightweight advanced open model series launched by Google, built on the same research and technology as the Gemini models. This model is multimodal, capable of processing both text and image inputs to generate text outputs.

BLIP is a unified vision-language pretraining framework, excelling in visual question answering tasks through joint language-image training to achieve multimodal understanding and generation capabilities

A vision-language model trained on the LAION-2B English dataset based on the OpenCLIP framework, supporting zero-shot image classification and cross-modal retrieval tasks

A vision-language model trained on the English subset of LAION-2B using the OpenCLIP framework, supporting zero-shot image classification and cross-modal retrieval

PickScore v1 is a scoring function for text-to-image generation, used to predict human preferences, evaluate model performance, and rank images.

OWLv2 is a zero-shot text-conditioned object detection model that can localize objects in images through text queries.

Llama 3.2 is a multilingual, multimodal large language model released by Meta, supporting image-to-text and text-to-text conversion tasks with robust cross-modal understanding capabilities.

OWL-ViT is a zero-shot text-conditioned object detection model that can search for objects in images via text queries without requiring category-specific training data.