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liked a model 25 days ago

oumoumad/Qwen-Edit-2509-Material-transfer

liked a model 25 days ago

peteromallet/Qwen-Image-Edit-InScene

liked a model 4 months ago

rockerBOO/flux.1-dev-SRPO

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liked 2 models 25 days ago

oumoumad/Qwen-Edit-2509-Material-transfer

Image-to-Image • Updated 25 days ago • 32

peteromallet/Qwen-Image-Edit-InScene

Image-to-Image • Updated Nov 1 • 1.85k • 85

liked a model 4 months ago

rockerBOO/flux.1-dev-SRPO

Text-to-Image • Updated Oct 8 • 1.95k • 67

liked a model 6 months ago

orabazes/depth_lora_kontext

Updated Jun 30 • 30

reacted to ZhengPeng7's post with 👍 8 months ago

Post

6558

We just released the [BiRefNet_HR]( ZhengPeng7/BiRefNet_HR) for general use on higher resolution images, which was trained with images in 2048x2048. If your images are mostly larger than 1024x1024, use BiRefNet_HR for better results! Thanks to @Freepik for the kind support of H200s for this huge training.

HF Model: ZhengPeng7/BiRefNet_HR.
HF Demo: ZhengPeng7/BiRefNet_demo, where you need to choose General-HR and set high resolution.
PyTorch weights & ONNX: in Google Drive and the GitHub release.

Here is a comparison between the results of the original one and the new HR one on HR inputs:

And, the performance of this new HR one and the previous one trained in 1024x1024 on val set:

liked a model 9 months ago

lldacing/flash-attention-windows-wheel

Updated May 31 • 288

liked 2 models 12 months ago

wei112/ziyong

Updated Aug 8, 2024 • 2

whitealan/WhitePony

Updated Dec 29, 2024 • 22

liked a model about 1 year ago

mattmdjaga/segformer_b2_clothes

Image Segmentation • 27.4M • Updated Sep 19 • 133k • • 471

liked a Space about 1 year ago

BRIA RMBG 2.0

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858

remove background from any image

reacted to clem's post with ❤️ about 1 year ago

Post

3740

Very few people realize that most of the successful AI startups got successful because they were focused on open science and open-source for at least their first few years. To name but a few, OpenAI (GPT, GPT2 was open-source), Runway & Stability (stable diffusion), Cohere, Mistral and of course Hugging Face!

The reasons are not just altruistic, it's also because sharing your science and your models pushes you to build AI faster (which is key in a fast-moving domain like AI), attracts the best scientists & engineers and generates much more visibility, usage and community contributions than if you were 100% closed-source. The same applies to big tech companies as we're seeing with Meta and Google!

More startups and companies should release research & open-source AI, it's not just good for the world but also increases their probability of success!