ptranking: Improve Ranking
Ptranking is a PyTorch-based library for learning to rank, which enables the development of custom ranking models for information retrieval and other applications.
- •Building a search engine that requires a custom ranking algorithm
- •Developing a recommendation system that needs to prioritize items based on user behavior
- •Creating a question answering model that requires ranking potential answers
python ptranking/train.py -cfg configs/example.cfg -model ListingLR -data MovieLens -metric NDCG
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/ptranking && curl -fsSL https://workflowstacks.com/api/skills/ptranking/claude-skill -o ~/.claude/skills/ptranking/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Ptranking: Improve Ranking is mostly documents (16 doc files, 115 small scripts) — something you read, not something you run. There is nothing to install. Last commit 50 months ago, MIT license.
- 1README.mdStart here — what it does and how to install it
- 2ptranking/__init__.pyInside ptranking/ — the main logic begins here
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/ptranking && curl -fsSL https://workflowstacks.com/api/skills/ptranking/claude-skill -o ~/.claude/skills/ptranking/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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Rank Tracker
A weekly email of where you actually rank on Google.
Includes the tested workflow and a written setup playbook. Needs: SerpAPI key (free tier).
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