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xziayro

xziayro

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reacted to freddyaboulton's post with 🚀 12 days ago

Getting WebRTC and Websockets right in python is very tricky. If you've tried to wrap an LLM in a real-time audio layer then you know what I'm talking about. That's where FastRTC comes in! It makes WebRTC and Websocket streams super easy with minimal code and overhead. Check out our org: hf.co/fastrtc

upvoted a paper 12 days ago

K-LoRA: Unlocking Training-Free Fusion of Any Subject and Style LoRAs

upvoted a paper 12 days ago

ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generation

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reacted to freddyaboulton's post with 🚀 12 days ago

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3114

Getting WebRTC and Websockets right in python is very tricky. If you've tried to wrap an LLM in a real-time audio layer then you know what I'm talking about.

That's where FastRTC comes in! It makes WebRTC and Websocket streams super easy with minimal code and overhead.

Check out our org: hf.co/fastrtc

upvoted 4 papers 12 days ago

K-LoRA: Unlocking Training-Free Fusion of Any Subject and Style LoRAs

Paper • 2502.18461 • Published 12 days ago • 15

ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generation

Paper • 2502.18364 • Published 13 days ago • 32

KV-Edit: Training-Free Image Editing for Precise Background Preservation

Paper • 2502.17363 • Published 14 days ago • 32

SpargeAttn: Accurate Sparse Attention Accelerating Any Model Inference

Paper • 2502.18137 • Published 13 days ago • 51

liked a model 14 days ago

ZhengPeng7/BiRefNet_HR

Image Segmentation • Updated 14 days ago • 23k • 60

liked a model 15 days ago

fffiloni/deep-blue-v2

Text-to-Image • Updated 17 days ago • 358 • • 8

upvoted a paper 18 days ago

Craw4LLM: Efficient Web Crawling for LLM Pretraining

Paper • 2502.13347 • Published 19 days ago • 27

liked a model 18 days ago

fffiloni/sweet-brush

Text-to-Image • Updated 14 days ago • 450 • • 5

liked a dataset 18 days ago

google/smol

Viewer • Updated 6 days ago • 811k • 3.63k • 44

reacted to sayakpaul's post with 🔥 20 days ago

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3030

Inference-time scaling meets Flux.1-Dev (and others) 🔥

Presenting a simple re-implementation of "Inference-time scaling diffusion models beyond denoising steps" by Ma et al.

I did the simplest random search strategy, but results can potentially be improved with better-guided search methods.

Supports Gemini 2 Flash & Qwen2.5 as verifiers for "LLMGrading" 🤗

The steps are simple:

For each round:

1> Starting by sampling 2 starting noises with different seeds.
2> Score the generations w.r.t a metric.
3> Obtain the best generation from the current round.

If you have more compute budget, go to the next search round. Scale the noise pool (2 ** search_round) and repeat 1 - 3.

This constitutes the random search method as done in the paper by Google DeepMind.

Code, more results, and a bunch of other stuff are in the repository. Check it out here: https://github.com/sayakpaul/tt-scale-flux/ 🤗