3+ week, 2+ day ago   (648+ words) This tutorial provides an end-to-end workflow for fine-tuning language models using Direct Preference Optimization (DPO). We demonstrate how to audit the Anthropic HH-RLHF dataset for structural and length-based biases, implement a robust training pipeline using TRL and LoRA, and evaluate…...

2+ mon, 2+ week ago   (550+ words) The research team trained GLM-5 on SWE tasks at up to 131k sequence length. Step times stayed under five minutes. The batch size was 256 rollouts. The run used only 28 H200 nodes. prime-rl is an open framework for asynchronous reinforcement learning. It post-trains…...

4+ mon, 1+ week ago   (575+ words) In this tutorial, we walk through a complete, hands-on journey of post-training large language models using the powerful TRL (Transformer Reinforcement Learning) library ecosystem. We start from a lightweight base model and progressively apply four key techniques: Supervised Fine-Tuning (SFT),…...

4+ mon, 2+ week ago   (271+ words) We construct a synthetic long-term memory bank that simulates stored knowledge across multiple domains. We generate structured memory items and convert them into textual memories that can later be embedded for semantic retrieval. We also create query datasets from these…...

4+ mon, 3+ week ago   (883+ words) Hugging Face has released ml-intern, an open-source AI agent designed to automate end-to-end post-training workflows for large language models (LLMs). Built on the company’s smolagents framework, the tool can autonomously perform literature review, dataset discovery, training script execution, and iterative…...

4+ mon, 4+ week ago   (840+ words) Standardized tests can tell you whether a student knows calculus or can parse a passage of text. What they cannot reliably tell you is whether that student can resolve a disagreement with a teammate, generate genuinely original ideas under pressure,…...

5+ mon, 1+ week ago   (223+ words) In the early stages of the LLM boom, post-training was often treated as an experimental ‘dark art.’ TRL v1.0 aims to change that by providing a consistent developer experience built on three core pillars: a dedicated Command Line Interface (CLI), a…...

5+ mon, 3+ week ago   (971+ words) Mistral AI has released Mistral Small 4, a new model in the Mistral Small family designed to consolidate several previously separate capabilities into a single deployment target. Mistral team describes Small 4 as its first model to combine the roles associated with…...

7+ mon, 2+ day ago   (229+ words) We set up the execution environment and ensure all required dependencies are installed dynamically. We initialize PyTorch, einops, and utility helpers that standardize device selection and shape inspection. We also establish reusable printing utilities that help us track tensor shapes…...

7+ mon, 1+ week ago   (315+ words) We set up the execution environment and installed all required dependencies. We initialize random seeds and device settings to maintain reproducibility across experiments. We also load the MNIST dataset, which serves as a lightweight yet effective benchmark for federated learning…...