deepseek r1 grpo bounty complete__ open source flywheel at work. evaluations complete, training runs in progress, benchmarks imminent, gpus go brrr__

to relign__ to realign a base model into a reasoning model, effectively teaching it how to think in steps. see also: taking the red pill, a baby walking, pulling back the curtain, emerging from the cave, returning to zero, peering behind the veil. first framework benchmarks incoming__

about multi-step learning inference__ a multi-step learning inference strategy decomposes complex tasks into smaller, sequential steps. at each step, the model refines its understanding, incorporates previous results, and guides its reasoning. this iterative approach enables much deeper analysis, reduces error propagation, and fosters substantially more accurate decisions or predictions compared to single-step methods. GRPO math benchmarks loading__

new developer bounty__ implement a multi-step learning inference strategy 250K $RELIGN__

RT @adamcreates_: open source flywheel: 1. work on difficult problems 2. difficult problems attract high-caliber talent 3. high-caliber ta…

democratize reasoning__

new developer bounty__ create a complex medical reasoning task specification + verifier based on HuatuoGPT-o1. 250K $RELIGN dataset+paper: __

RT @promptpapi: builders market

the relign framework turns base models into reasoning models__ this allows all ai applications built on top of these models to think harder about complex problems, improving performance and output. relign is framework agnostic, and as such can be utilized to post train any open source base model. ___

deepseek GRPO implementation in progress__ GRPO (group relative policy optimization) is the core rl algorithm that was used to drive deepseek reasoning abilities. it is a reinforcement learning algorithm used to help a model learn better by comparing different actions and making small, controlled updates using a set of observations. a smart way to learn from experience without making drastic changes that could interfere with the goals of the training. developer bounty program active. ___

vision__ to empower ai researchers and developers with cutting-edge RL frameworks and open source data-sets, enabling them to solve important problems and build the next generation of artificial intelligence applications. go alone, go fast. go together, go far. ___

roadmap__ phase i - launch__complete phase ii - develop a strong reasoning library | grpo, full docs, whitepaper, modularization, expand reasoning stack, expand dev community phase iii - scaling up | cloud runner, 70B+ parameter reasoning model, relign toolkit, research program, reasoning-as-a-service platform

relign gitbook v1 live - covering concept, vision, mission, roadmap, use cases notable quote: relign is a step towards artificial general intelligence. the technology has far-reaching application, because it is a fundamental tool that teaches base models how to think. This allows the reasoning model to do anything a human is capable of - scientific research, software engineering, financial analysis, psychological analysis, the list goes on. reasoning models don't have a defined list of use cases. it is the future.

@naklecha hey, we're working on an open source post training framework for os llm's. would love to get you involved ___

@BoochaoNA1 @bookwormengr hey @BoochaoNA1 we're working on an open source post training framework for os llm's, would love to get you involved ___

@theanakin87 @picampusschool hey @theanakin87 we're working on an open source post training framework for os llm's, would love to get you involved ___

@nickcdryan hey @nickcdryan we're working on an open source post training framework for os llm's, would love to get you involved ___

@lateinteraction hey @omarkhattab we're working on an open source post training framework for os llm's, would love to get you involved ___

@xlr8harder hey @xlr8harder we're working on an open source post training framework for os llm's, would love to get you involved ___