Yu li

Yukkkop

AI & ML interests

None yet

Recent Activity

liked a model about 3 hours ago

amphion/Vevo

liked a Space about 3 hours ago

amphion/Vevo

liked a model 1 day ago

sand-ai/MAGI-1

View all activity

Organizations

None yet

Yukkkop's activity

liked a model about 3 hours ago

amphion/Vevo

Text-to-Speech • Updated 10 days ago • 25 • 30

liked a Space about 3 hours ago

Vevo for Zero-shot VC, TTS, and More

🐠

Controllable Zero-Shot Voice Imitation

liked a model 1 day ago

sand-ai/MAGI-1

Image-to-Video • Updated 1 day ago • 180

upvoted a paper 2 days ago

DMM: Building a Versatile Image Generation Model via Distillation-Based Model Merging

Paper • 2504.12364 • Published 6 days ago • 17

liked a model 2 days ago

diffusers/stable-diffusion-xl-1.0-inpainting-0.1

Text-to-Image • Updated Sep 3, 2023 • 687k • 331

liked 3 Spaces 2 days ago

Zen Style Shape

🔥

Structure-Preserving Style Transfer with Canny, Depth & Flux

Lightning Painter (In n' Out)

⚡

Lightning fast 5-sec inpainting and outpainting, uncensored.

ThinkFlow

🐨

thought that reasoning into LLMs without modification

reacted to merterbak's post with 🔥 2 days ago

Post

1888

Here’s a cool paper I found: “Massive Image Embedding Benchmark (MIEB).” It is a new tool to test how good image embedding models are. It has 130 different tasks grouped into 8 categories, like image search, classification, clustering similar images, answering questions based on images, and understanding documents. It even covers 38 different languages.

The authors tested 50 models and found that no single model was best at everything. Some models were great at recognizing text inside images but struggled to handle complicated tasks like matching images and text that appear together.

Paper: https://arxiv.org/pdf/2504.10471v1
Code: https://github.com/embeddings-benchmark/mteb

2 replies

reacted to Jaward's post with 🤗 2 days ago

Post

2534

nice clean GRPO implementation:
- no transformers
- no vllm
- has improved grpo (DAPO)
- under 300 lines
- runs on 24GB (RTX 4090 GPU)
Code: https://github.com/policy-gradient/GRPO-Zero