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Discover the best community collections!

Collections including paper arxiv:2405.02246

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6 • 22
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6 • 10
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7 • 33
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 19

Idefics2-8B is a foundation vision-language model. In this collection, you will find the models, datasets and demo related to its creation.

Running on Zero

159

🐨

IDEFICS2 Playground
HuggingFaceM4/idefics2-8b

Image-Text-to-Text • Updated May 30 • 727k • 541
HuggingFaceM4/idefics2-8b-chatty

Image-Text-to-Text • Updated May 30 • 16k • 81
HuggingFaceM4/idefics2-8b-base

Image-Text-to-Text • Updated May 30 • 5.93k • 26

Vision-language model (VLMs)

What matters when building vision-language models?

Paper • 2405.02246 • Published May 3 • 93
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 78
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output

Paper • 2407.03320 • Published 19 days ago • 87

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Paper • 2406.06525 • Published Jun 10 • 62
Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning

Paper • 2406.06469 • Published Jun 10 • 22
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

Paper • 2406.04271 • Published Jun 6 • 27
Block Transformer: Global-to-Local Language Modeling for Fast Inference

Paper • 2406.02657 • Published Jun 4 • 36

What matters when building vision-language models?

Paper • 2405.02246 • Published May 3 • 93

What matters when building vision-language models?

Paper • 2405.02246 • Published May 3 • 93

What matters when building vision-language models?

Paper • 2405.02246 • Published May 3 • 93
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 78
DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark

Paper • 2405.19707 • Published May 30 • 4

MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training

Paper • 2311.17049 • Published Nov 28, 2023
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7 • 12
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision

Paper • 2303.17376 • Published Mar 30, 2023
Sigmoid Loss for Language Image Pre-Training

Paper • 2303.15343 • Published Mar 27, 2023 • 4

image llm works

Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation

Paper • 2404.19752 • Published Apr 30 • 21
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Paper • 2404.16821 • Published Apr 25 • 52
MoAI: Mixture of All Intelligence for Large Language and Vision Models

Paper • 2403.07508 • Published Mar 12 • 73
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Paper • 2403.09611 • Published Mar 14 • 123

What matters when building vision-language models?

Paper • 2405.02246 • Published May 3 • 93

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