HuggingFace Experiment Tracking

github.com/huggingface/skills

Track experiments, metrics, and model performance across training runs for reproducible AI research.

HuggingFace Datasets

github.com/huggingface/skills

Manage, load, and process datasets from HuggingFace Hub for machine learning training and evaluation.

HuggingFace Model Trainer

github.com/huggingface/skills

Comprehensive training tools for fine-tuning and training AI models with best practices and optimization strategies.

Hook OpenCode Go into Codex on Windows. Do Not Open a Second Toolkit.

A ChatGPT-signed Codex desktop app still shows mostly GPT in the picker. On Windows, enable only OpenCode Go and the Grok, GLM, Kimi, DeepSeek, and MiniMax models you already pay for appear in the same selector. Keys stay local. Native GPT stays put.

What Locks Codex Is the Picker, Not the Models

You already pay for OpenCode Go, Grok, and Z.ai, but the Codex picker still shows mostly GPT. The community project codex-router does not teach another install ritual. It puts subscriptions you already bought back into the selector, keeps keys on the machine, and leaves native GPT alone.

Seven AI Coding CLIs, Six Months: No Matter How Strong the Model, Work Needs Supervision

Claude Code, Codex, opencode, pi, omp and DeepSeek Harness all have personalities. After six months of deep use I run a division of labor: pi for the fastest cheapest reviews, omp for complex PRs, DeepSeek Harness on V4 Flash for high-frequency low-cost review, and Claude Code, Qoder and Cursor for writing. No matter how strong the model, work needs supervision — ideally from an independent third party.