tensorflow-guide
TensorFlow best practices for tf.function, GPU memory, and deployment
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tensorflow-guide --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# TensorFlow Guide ## Overview TensorFlow is a production-grade machine learning framework that excels at deployment, distributed training, and hardware acceleration. While PyTorch dominates pure research prototyping, TensorFlow remains the standard in industry ML systems and is heavily used in applied research where models must move from experiment to production. TensorFlow 2.x unified eager exec
What does the tensorflow-guide skill do?
TensorFlow best practices for tf.function, GPU memory, and deployment
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tensorflow-guide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.