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README.md

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+# Welcome to Open-R1 🐳🤗
+Open-R1 is an open initiative to replicate and extend the techniques behind DeepSeek-R1, a state-of-the-art reasoning model, in a fully transparent and collaborative way. This organization is dedicated to:
+- Sharing datasets and models built on the path to replicating DeepSeek-R1.
+- Fostering meaningful discussions and collaboration in the Discussion tab.
+By working together, we aim to create a robust foundation for reasoning models that the entire research and industry community can leverage.
+
+# Plan of attack
+We are using the DeepSeek-R1 tech report as a guide to recreate their pipeline. The work can be broken down into three main steps:
+
+- Replicate R1-Distill:
+Distill a high-quality reasoning corpus from DeepSeek-R1 to create the R1-Distill models.
+- Recreate the pure RL pipeline:
+Reproduce the reinforcement learning process that DeepSeek used to train R1-Zero. This will likely require curating new, large-scale datasets for math, reasoning, and code.
+- Demonstrate end-to-end training:
+Show that we can go from a base model to RL-tuned reasoning capabilities through a multi-stage training approach, combining supervised fine-tuning (SFT) and reinforcement learning (RL).
+
+# How to contribute
+This project thrives on community participation! Here are some ways you can contribute:
+- Join the Discussion: Share ideas, ask questions, and collaborate with others in the Discussion tab.
+- Contribute Code or Datasets: Submit pull requests with datasets, models, or improvements to the pipeline.
+- Experiment and Share Results: Try out different approaches and share your findings with the community.
+Let’s build something impactful together. 🚀
 
-Edit this `README.md` markdown file to author your organization card.