Donate your coding sessions to an open CC-BY-4.0 dataset to help train open-weight and open source models
Summary
A new initiative called Trace Commons aims to collect coding agent traces into an open CC-BY-4.0 dataset to help train open-weight and open-source models, countering the data advantage of proprietary models from Anthropic and OpenAI.
Similar Articles
@ClementDelangue: We need open traces so that everyone can train open agent models! cc @steipete @badlogicgames @thdxr @matanSF @hwchase17
Clement Delangue advocates for open traces to democratize training of open agent models.
@kevin_x_li: Introducing SWE-ZERO-12M-trajectories: the largest agentic trace dataset in the open, 5.7x larger than the previous lar…
SWE-ZERO-12M-trajectories is the largest open agentic trace dataset for coding, with 112B tokens across 12M trajectories from 122K pull requests and 3K repositories, enabling scalable training of agentic coding models without requiring containerized execution.
LocalLLaMA crowdsourced coding dataset
A community member proposes creating a crowdsourced coding dataset for local LLMs to enable collaborative model training and fine-tuning, addressing concerns about future availability of open-weight models.
Open weights are not open source: Why AI's favorite label is under dispute
The article debates the misuse of 'open source' for AI models that only release weights, emphasizing that true open source requires access to training data and processes for accountability.
I built a tool to turn your Claude Code sessions into fine-tuning data for local models
A new open-source tool called claude_converter converts Claude Code session logs into fine-tuning datasets compatible with TRL/SFTTrainer, Axolotl, and LLaMA-Factory, enabling developers to repurpose real coding conversations for training local models.