for those afraid of using a chinese ai or want to more easily build more powerful ais based on deepseek's r1:

"The release of DeepSeek-R1 is an amazing boon for the community, but they didn’t release everything—although the model weights are open, the datasets and code used to train the model are not.

The goal of Open-R1 is to build these last missing pieces so that the whole research and industry community can build similar or better models using these recipes and datasets. And by doing this in the open, everybody in the community can contribute!.

As shown in the figure below, here’s our plan of attack:

Step 1: Replicate the R1-Distill models by distilling a high-quality reasoning dataset from DeepSeek-R1.

Step 2: Replicate the pure RL pipeline that DeepSeek used to create R1-Zero. This will involve curating new, large-scale datasets for math, reasoning, and code.

Step 3: Show we can go from base model → SFT → RL via multi-stage training.

The synthetic datasets will allow everybody to fine-tune existing or new LLMs into reasoning models by simply fine-tuning on them. The training recipes involving RL will serve as a starting point for anybody to build similar models from scratch and will allow researchers to build even more advanced methods on top."

https://huggingface.co/blog/open-r1?utm_source=tldrai#what-is-deepseek-r1