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facebook/dinov3-vit7b16-pretrain-lvd1689m
Image Feature Extraction • 7B • Updated • 9.47k • 225 -
facebook/dinov3-vits16-pretrain-lvd1689m
Image Feature Extraction • 21.6M • Updated • 347k • 85 -
facebook/dinov3-convnext-small-pretrain-lvd1689m
Image Feature Extraction • 49.5M • Updated • 15.7k • 26 -
facebook/dinov3-vitb16-pretrain-lvd1689m
Image Feature Extraction • 85.7M • Updated • 1.39M • 118
Collections
Discover the best community collections!
Collections including paper arxiv:2508.10104
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ViViT: A Video Vision Transformer
Paper • 2103.15691 • Published • 4 -
DINO-Foresight: Looking into the Future with DINO
Paper • 2412.11673 • Published • 1 -
Scaling Behavior Cloning Improves Causal Reasoning: An Open Model for Real-Time Video Game Playing
Paper • 2601.04575 • Published • 12 -
Learning Long-Context Diffusion Policies via Past-Token Prediction
Paper • 2505.09561 • Published
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Attention Is All You Need
Paper • 1706.03762 • Published • 121 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 10 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
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A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale
Paper • 2309.06497 • Published • 7 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 251
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Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 282 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 265 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 254 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 263
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facebook/dinov3-vit7b16-pretrain-lvd1689m
Image Feature Extraction • 7B • Updated • 9.47k • 225 -
facebook/dinov3-vits16-pretrain-lvd1689m
Image Feature Extraction • 21.6M • Updated • 347k • 85 -
facebook/dinov3-convnext-small-pretrain-lvd1689m
Image Feature Extraction • 49.5M • Updated • 15.7k • 26 -
facebook/dinov3-vitb16-pretrain-lvd1689m
Image Feature Extraction • 85.7M • Updated • 1.39M • 118
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Attention Is All You Need
Paper • 1706.03762 • Published • 121 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 10 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
-
ViViT: A Video Vision Transformer
Paper • 2103.15691 • Published • 4 -
DINO-Foresight: Looking into the Future with DINO
Paper • 2412.11673 • Published • 1 -
Scaling Behavior Cloning Improves Causal Reasoning: An Open Model for Real-Time Video Game Playing
Paper • 2601.04575 • Published • 12 -
Learning Long-Context Diffusion Policies via Past-Token Prediction
Paper • 2505.09561 • Published
-
A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale
Paper • 2309.06497 • Published • 7 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 251
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 282 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 265 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 254 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 263