MMLForge Search models, datasets, tasks… Start free
Home › Models › Zero Shot Image Classification › wisdomik/QuiltNet-B-32
Q

wisdomik/QuiltNet-B-32

Zero Shot Image Classification·wisdomik· 36.2K· 28
open_clip mit Zero Shot Image Classification arxiv:2306.11207license:mitregion:us

QuiltNet-B-32 is a CLIP ViT-B/32 vision-language foundation model trained on the Quilt-1M dataset curated from representative histopathology videos. It can perform various vision-language processing (VLP) tasks such as cross-modal retrieval, image classification, and visual question answering. QuiltNet establishes new state of the art in a wide range of standard datasets, and substantially outper

Open in MLForge Sign up free Desktop app Source ↗
# pull & run locally
pip install mlforge-sdk && mlforge pull wisdomik/QuiltNet-B-32

Model details

Task
Zero Shot Image Classification
Provider
wisdomik
Framework
open_clip
Size
2.9 GB
License
mit
Downloads
36.2K
Likes
28
Paper
arXiv:2306.11207
Updated
2023-10-23

About wisdomik/QuiltNet-B-32

QuiltNet-B-32 is a CLIP ViT-B/32 vision-language foundation model trained on the Quilt-1M dataset curated from representative histopathology videos. It can perform various vision-language processing (VLP) tasks such as cross-modal retrieval, image classification, and visual question answering. QuiltNet establishes new state of the art in a wide range of standard datasets, and substantially outperforms prior VLP approaches:

Related Zero Shot Image Classification

C openai/clip-vit-base-patch32 Zero Shot Image Classification 22.8M 966 🤗 HF C openai/clip-vit-large-patch14 Zero Shot Image Classification ·427.6M params 12.0M 2.0K 🤗 HF C laion/CLIP-ViT-B-32-laion2B-s34B-b79K Zero Shot Image Classification ·151.3M params 3.8M 141 🤗 HF P yuvalkirstain/PickScore_v1 Zero Shot Image Classification ·986.1M params 3.2M 52 🤗 HF F patrickjohncyh/fashion-clip Zero Shot Image Classification ·151.3M params 2.9M 284 🤗 HF C openai/clip-vit-large-patch14-336 Zero Shot Image Classification 2.8M 308 🤗 HF

Browse all Zero Shot Image Classification models →