awesome!
Zixi "Oz" Li
OzTianlu
AI & ML interests
My research focuses on deep reasoning with small language models, Transformer architecture innovation, and knowledge distillation for efficient alignment and transfer.
Recent Activity
liked
a model
5 minutes ago
NoesisLab/Geilim-1B-Instruct
updated
a model
7 minutes ago
NoesisLab/Geilim-1B-Instruct
updated
a collection
11 minutes ago
Geilim Large Language Models
Organizations
replied to
sergiopaniego's
post
about 2 hours ago
reacted to
sergiopaniego's
post with 🔥
about 2 hours ago
Post
858
New TRL + OpenEnv example! 💥
Fine tune an LLM for playing Sudoku using an RL env via OpenEnv
Includes a script that runs on 1 or multiple GPUs with vLLM, plus a Colab-ready notebook.
Enjoy!
Notebook: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/openenv_sudoku_grpo.ipynb
Script: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/sudoku.py
Fine tune an LLM for playing Sudoku using an RL env via OpenEnv
Includes a script that runs on 1 or multiple GPUs with vLLM, plus a Colab-ready notebook.
Enjoy!
Notebook: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/openenv_sudoku_grpo.ipynb
Script: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/sudoku.py
-
- 1 reply
reacted to
imnotkitty's
post with 🔥
about 7 hours ago
Post
1693
📌Same day, Two Releases.
Jan 27th just got interesting on Open-source AI modles.
✅Kimi K2.5: How to make models "think" across text and vision natively?
moonshotai/Kimi-K2.5
✅DeepSeek-OCR 2: How to make models "see" more like humans, not scanners?
deepseek-ai/DeepSeek-OCR-2
One focuses on depth of reasoning, the other on precision of vision.
What's the key differentiator for a multimodal model in your view: raw power or computational elegance?
Jan 27th just got interesting on Open-source AI modles.
✅Kimi K2.5: How to make models "think" across text and vision natively?
moonshotai/Kimi-K2.5
✅DeepSeek-OCR 2: How to make models "see" more like humans, not scanners?
deepseek-ai/DeepSeek-OCR-2
One focuses on depth of reasoning, the other on precision of vision.
What's the key differentiator for a multimodal model in your view: raw power or computational elegance?
reacted to
their
post with ❤️
9 days ago
Post
1181
🚀 Introducing Asterisk — Hybrid ASPP-Attention Architecture! 🌟
NoesisLab/Asterisk
We’re excited to launch Asterisk, a cutting-edge language model by NoesisLab on Hugging Face! 🎉 Built on top of SmolLM2-135M-Instruct, Asterisk integrates Adjacency-Structured Parallel Propagation (ASPP) with standard attention to bring structured reasoning power into language modeling.
✨ Key Highlights:
🔹 Hybrid Architecture – Fuses graph-centric ASPP local reasoning with global attention for richer representations.
🔹 Enhanced Reasoning – ASPP enables iterative local state evolution that complements traditional transformer layers.
🔹 Efficient Design – ~171M parameters with smart supervised fine-tuning (Capybara dataset).
🔹 Flexible & Open – Apache-2.0 licensed and ready to integrate via Hugging Face 🤗 Transformers.
📈 Asterisk showcases how hybrid operators — inspired by theoretical frameworks like the Asterisk Operator — can bring structured reasoning into modern LMs in a scalable way.
👉 Try it out, explore the code, and start building: huggingface.co/NoesisLab/Asterisk
- 1 reply
posted
an
update
10 days ago
Post
1181
🚀 Introducing Asterisk — Hybrid ASPP-Attention Architecture! 🌟
NoesisLab/Asterisk
We’re excited to launch Asterisk, a cutting-edge language model by NoesisLab on Hugging Face! 🎉 Built on top of SmolLM2-135M-Instruct, Asterisk integrates Adjacency-Structured Parallel Propagation (ASPP) with standard attention to bring structured reasoning power into language modeling.
✨ Key Highlights:
🔹 Hybrid Architecture – Fuses graph-centric ASPP local reasoning with global attention for richer representations.
🔹 Enhanced Reasoning – ASPP enables iterative local state evolution that complements traditional transformer layers.
🔹 Efficient Design – ~171M parameters with smart supervised fine-tuning (Capybara dataset).
🔹 Flexible & Open – Apache-2.0 licensed and ready to integrate via Hugging Face 🤗 Transformers.
📈 Asterisk showcases how hybrid operators — inspired by theoretical frameworks like the Asterisk Operator — can bring structured reasoning into modern LMs in a scalable way.
👉 Try it out, explore the code, and start building: huggingface.co/NoesisLab/Asterisk
-
- 1 reply