Qwen

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https://qwen.ai/

alibaba_qwen

QwenLM

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Recent Activity

SaylorTwift new activity 5 days ago

Qwen/Qwen3-ASR-0.6B:Add Open ASR Leaderboard evaluation results

SaylorTwift new activity 5 days ago

Qwen/Qwen3-ASR-0.6B:Add Open ASR Leaderboard evaluation results

akhaliq submitted a paper 9 days ago

MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines

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Papers

RealChart2Code: Advancing Chart-to-Code Generation with Real Data and Multi-Task Evaluation

Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs

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danielhanchen

posted an update 5 days ago

Post

5037

You can now fine-tune Gemma 4 for free with our notebooks! 🔥

You just need 8GB VRAM to train Gemma 4 locally!

Unsloth trains Gemma4 1.5x faster with 50% less VRAM.
GitHub: https://github.com/unslothai/unsloth
Guide + Notebooks: https://unsloth.ai/docs/models/gemma-4/train

5 replies

SaylorTwift

in Qwen/Qwen3-ASR-0.6B 5 days ago

Add Open ASR Leaderboard evaluation results

#11 opened 5 days ago by

SaylorTwift

Add Open ASR Leaderboard evaluation results

#10 opened 5 days ago by

SaylorTwift

akhaliq

submitted a paper to Daily Papers 9 days ago

MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines

Paper • 2603.06679 • Published 14 days ago • 5

danielhanchen

posted an update 10 days ago

Post

3626

Google releases Gemma 4. ✨
Gemma 4 introduces 4 models: E2B, E4B, 26B-A4B, 31B.
The multimodal reasoning models are under Apache 2.0.

Run E2B and E4B on ~6GB RAM, and on phones. Run 26B-A4B and 31B on ~18GB.

GGUFs: https://huggingface.co/collections/unsloth/gemma-4
Guide: https://unsloth.ai/docs/models/gemma-4

SaylorTwift

in Qwen/Qwen3-ASR-1.7B 11 days ago

Add Open ASR Leaderboard evaluation results

#20 opened 11 days ago by

SaylorTwift

737443h

submitted a paper to Daily Papers 12 days ago

FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization

Paper • 2603.19835 • Published 24 days ago • 330

danielhanchen

posted an update 12 days ago

Post

2641

A new way to use Unsloth.

Coming soon...

zjj1233

submitted a paper to Daily Papers 14 days ago

RealChart2Code: Advancing Chart-to-Code Generation with Real Data and Multi-Task Evaluation

Paper • 2603.25804 • Published 17 days ago • 29

VoyagerXHF

updated 2 Spaces 14 days ago

Qwen3.5 Omni Offline Demo

🌍

119

Chat with a multimodal AI using text, images, audio, or video

Qwen3.5 Omni Online Demo

📚

Chat with a multimodal AI using text, image, audio, or video

akhaliq

submitted a paper to Daily Papers 16 days ago

AVO: Agentic Variation Operators for Autonomous Evolutionary Search

Paper • 2603.24517 • Published 18 days ago • 10

danielhanchen

posted an update 18 days ago

Post

868

You don’t need to set LLM parameters anymore! 🚀

llama.cpp uses only the context length + compute your local setup needs. Unsloth also auto-applies the correct model settings

Try in Unsloth Studio - now with precompiled llama.cpp binaries.

GitHub: https://github.com/unslothai/unsloth