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This repository includes implementations to reproduce the R1 pipeline for code generation:
The main features of ganler/code-r1 are: Code and Formal Reasoning, Reasoning Datasets.
Open-source alternatives to ganler/code-r1 include: huggingface/open-r1 — Open-r1 is a framework designed for the large-scale training, distillation, and optimization of language models… skyworkai/skywork-or1 — ✊ Unleashing the Power of Reinforcement Learning for Math and Code Reasoners 🤖. microsoft/bosquelanguage — Bosque is an experimental programming language and development platform designed for machine-assisted software… alibaba-nlp/zerosearch — ZeroSearch: Incentivize the Search Capability of LLMs without Searching. deepseek-ai/deepseek-prover-v2. dataarctech/sql-r1 — SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning.
Open-r1 is a framework designed for the large-scale training, distillation, and optimization of language models focused on complex reasoning and programming tasks. It provides a comprehensive suite of tools for managing distributed training jobs across multi-node clusters, enabling the development of high-performance models through reinforcement learning and supervised fine-tuning. The project distinguishes itself by integrating secure, containerized code execution environments directly into the training and evaluation lifecycle. By allowing models to run and verify code snippets against test
✊ Unleashing the Power of Reinforcement Learning for Math and Code Reasoners 🤖
Bosque is an experimental programming language and development platform designed for machine-assisted software construction. It combines functional programming semantics with imperative syntax to enforce logic correctness and runtime safety, providing a type-safe environment that utilizes structured data models to maintain information integrity throughout the application lifecycle. The platform distinguishes itself through deep integration with formal verification tools, including automated theorem provers and symbolic execution engines. By transforming source code into a regularized intermed
ZeroSearch: Incentivize the Search Capability of LLMs without Searching