@lhoestq: The future is converting agent traces to SFT datasets. There is an amazing lib for this: pip install teich
Summary
A library called teich converts agent traces into supervised fine-tuning (SFT) datasets, simplifying dataset preparation for AI training.
View Cached Full Text
Cached at: 05/21/26, 01:32 PM
The future is converting agent traces to SFT datasets. There is an amazing lib for this: pip install teich https://t.co/pdFvSdXLmn
Similar Articles
ProCUA-SFT Technical Report
ProCUA-SFT is a large-scale synthetic dataset of 3.1M step-level SFT samples for training computer-use agents, produced via an automated pipeline using a single VLM (Kimi-K2.5). Fine-tuning UI-TARS 7B on it achieves 45.0% on OSWorld, an 18.7 point improvement over the base model.
@Vtrivedy10: there's a very exciting future agent recipe for building intelligence too cheap to meter, applied towards extracting si…
The post outlines a future agent recipe for building scalable intelligence by fine-tuning efficient, specialized open models to surpass frontier performance on LLM-as-a-judge tasks, and applying this to extract signals from trace data for continual learning. LangChain Labs and FireworksAI release new work demonstrating this approach.
@adithya_s_k: You can now finetune models on agent traces directly with TRL Claude Code traces Codex traces OpenClaw traces Pi traces…
TRL now supports fine-tuning models on agent traces from various sources like Claude Code, Codex, OpenClaw, and Pi, moving towards a standardized stack for training agentic models.
@martin_casado: This tackles a very hard, very important problem in AI systems. Basically how do you expose your traces at scale to age…
A tweet by Martin Casado highlighting a solution to the difficult problem of exposing traces at scale to AI agents, balancing cost and AI leverage.
@itsolelehmann: I remember in 2023-24 having to duct-tape so many different tools together to get half-decent AI outputs GPT 4 for writ…
Reflecting on the fragmented AI tool landscape of 2023-24, the user highlights the arrival of Higgsfield AI's Supercomputer, a cloud-native AI agent that consolidates 40+ tools for end-to-end task execution.