AI & ML interests

Evaluating open LLMs

Recent Activity

victor 
posted an update 7 days ago
view post
Post
4750
Want to share my enthusiasm for zai-org/GLM-5.1 here too 🔥

I think we have it: our open source Claude Code = GLM-5.1 + Pi (https://pi.dev/) - Built a Three.js racing game to eval and it's extremely impressive. Thoughts:

- One-shot car physics with real drift mechanics (this is hard)

- My fav part: Awesome at self iterating (with no vision!) created 20+ Bun.WebView debugging tools to drive the car programmatically and read game state. Proved a winding bug with vector math without ever seeing the screen

- 531-line racing AI in a single write: 4 personalities, curvature map, racing lines, tactical drifting. Built telemetry tools to compare player vs AI speed curves and data-tuned parameters

- All assets from scratch: 3D models, procedural textures, sky shader, engine sounds, spatial AI audio!

- Can do hard math: proved road normals pointed DOWN via vector cross products, computed track curvature normalized by arc length to tune AI cornering speed

You are going to hear about this model a lot in the next months - open source let's go - and thanks z-ai🚀🚀
  • 4 replies
·
albertvillanova 
posted an update about 2 months ago
view post
Post
2403
🚀 TRL v0.29.0 introduces trl-training: an agent-native training skill.

This makes the TRL CLI a structured, agent-readable capability, allowing AI agents to reliably execute training workflows such as:
- Supervised Fine-Tuning (SFT)
- Direct Preference Optimization (DPO)
- Group Relative Policy Optimization (GRPO)

We’re excited to see what the community builds on top of this.

If you’re working on AI agents, alignment research, or scalable RL training infrastructure: give TRL v0.29.0 a try! 🤗

The future of ML tooling is agent-native.
🔗 https://github.com/huggingface/trl/releases/tag/v0.29.0
AdinaY 
posted an update 2 months ago
view post
Post
3651
MiniMax M2.5 is now available on the hub 🚀

MiniMaxAI/MiniMax-M2.5

✨ 229B - Modified MIT license
✨37% faster than M2.1
✨ ~$1/hour at 100 TPS
  • 2 replies
·
AdinaY 
posted an update 2 months ago
AdinaY 
posted an update 2 months ago
view post
Post
4125
Game on 🎮🚀

While Seedance 2.0’s videos are all over the timeline, DeepSeek quietly pushed a new model update in its app.

GLM-5 from Z.ai adds more momentum.

Ming-flash-omni from Ant Group , MiniCPM-SALA from OpenBMB
, and the upcoming MiniMax M2.5 keep the heat on 🔥

Spring Festival is around the corner,
no one’s sleeping!

✨ More releases coming, stay tuned
https://huggingface.co/collections/zh-ai-community/2026-february-china-open-source-highlights
albertvillanova 
posted an update 2 months ago
view post
Post
1863
5 years already working in democratizing AI 🤗
Grateful to be part of such an awesome team making it happen every day.
AdinaY 
posted an update 2 months ago
view post
Post
3951
Ming-flash-omni 2.0 🚀 New open omni-MLLM released by Ant Group

inclusionAI/Ming-flash-omni-2.0

✨ MIT license
✨ MoE - 100B/6B active
✨ Zero-shot voice cloning + controllable audio
✨ Fine-grained visual knowledge grounding
  • 2 replies
·
AdinaY 
posted an update 2 months ago
view post
Post
803
LLaDA 2.1 is out 🔥 A new series of MoE diffusion language model released by AntGroup

inclusionAI/LLaDA2.1-mini
inclusionAI/LLaDA2.1-flash

✨LLaDA2.1-mini: 16B - Apache2.0
✨LLaDA2.1-flash: 100B - Apache2.0
✨Both delivers editable generation, RL-trained diffusion reasoning and fast inference
  • 2 replies
·
AdinaY 
posted an update 3 months ago
view post
Post
2620
AI for science is moving fast🚀

Intern-S1-Pro 🔬 a MoE multimodal scientific reasoning model from Shanghai AI Lab

internlm/Intern-S1-Pro

✨ 1T total / 22B active
✨ Apache 2.0
✨ SoTA scientific reasoning performance
✨ FoPE enables scalable modeling of long physical time series (10⁰–10⁶)
  • 2 replies
·
AdinaY 
posted an update 3 months ago
view post
Post
1409
✨ China’s open source AI ecosystem has entered a new phase

https://huggingface.co/blog/huggingface/one-year-since-the-deepseek-moment-blog-3

One year after the “DeepSeek Moment,” open source has become the default. Models, research, infrastructure, and deployment are increasingly shared to support large-scale, system-level integration.

This final blog examines how leading Chinese AI organizations are evolving ,and what this implies for the future of open source.