Getting Reasoning Models Enterprise Ready
Customize reasoning models with synthetic data generation for enterprise deployment. Learn techniques from Red Hat's AI Innovation Team.
A collective of researchers and engineers from Red Hat & IBM building LLM toolkits you can use today.
Inference-time scaling for LLMs.
Synthetic data generation pipelines
Post training algorithms for LLMs
Asynchronous GRPO for scalable reinforcement learning.
Efficient training library for large language models up to 70B parameters on a single node.
Adaptive SVD-based continual learning method for LLMs.
Inference-time scaling with particle filtering.
State-of-the-art reward models for preference data generation and acceptance criteria.
KV cache quantization for scaling inference time
Efficient messages-format SFT library for language models
Customize reasoning models with synthetic data generation for enterprise deployment. Learn techniques from Red Hat's AI Innovation Team.
Discover inference-time scaling techniques that improve AI quality and reliability for enterprise applications beyond just speed optimization.
Introducing Async-GRPO - an open-source library for scalable reinforcement learning with 42% efficiency gains over VERL and 11x over TRL for GRPO training.
👤 Speaker: Young Jin Park
👤 Speaker: Mustafa Eyceoz
👤 Speaker: Shivchander Sudalairaj & Abhishek Bhandwaldar