---
title: Tagline Foundry
emoji: 🏷️
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 5.12.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: Rate your tagline, then let a fine-tuned model beat it.
models:
  - standd/tagline-qwen3p5-4b
  - standd/tagline-quality-setfit
datasets:
  - standd/saas-taglines-rated
  - standd/saas-tagline-distilled
---

# 🏷️ Tagline Foundry

Paste a company URL. We render the landing page, grade your current hero tagline
against the five marks of a good one, then a **fine-tuned Qwen3.5-4B** writes sharper
alternatives — each scored 0–100 by a **SetFit** classifier.

## Why we built it

This exists to fix our *own* tagline. We make **[Hey Lefty](https://heylefty.com)** — an
autonomous research agent that briefs you every morning on any topic you follow (papers,
markets, regulators, competitors) and builds a compounding knowledge base while you do
your actual work. Our homepage hero just said *"Autonomous Research Agents"* — a
**category, not a tagline**. Rather than agonize over copy, we trained a model to write a
better one. Tagline Foundry is that pipeline, opened up for any site.

## How it works

1. **Render** — [lightpanda](https://lightpanda.io), an open-source headless browser, loads the page (with JS, so SPAs resolve).
2. **Extract** — the hero `<h1>` + `og:description` become your current tagline and the page context.
3. **Critique** — the model grades that line ✅/❌ on the five qualities; a SetFit classifier scores it 0–100.
4. **Rewrite** — a fine-tuned **Qwen3.5-4B**, *distilled from Claude Opus 4.7* as the teacher, drafts a dozen alternatives.
5. **Rank** — SetFit scores each; the strongest rise to the top.

The Space is free CPU; the GPU work runs on a **Modal** serverless endpoint that scales to
zero, so the first request after idle cold-starts (~60–90s) then runs fast.

## Open weights & data

- **Generator:** [standd/tagline-qwen3p5-4b](https://huggingface.co/standd/tagline-qwen3p5-4b) (Apache-2.0)
- **Quality scorer:** [standd/tagline-quality-setfit](https://huggingface.co/standd/tagline-quality-setfit)
- **Datasets:** [saas-taglines-rated](https://huggingface.co/datasets/standd/saas-taglines-rated) · [saas-tagline-distilled](https://huggingface.co/datasets/standd/saas-tagline-distilled)

Trained via Opus teacher distillation; on held-out companies it out-writes their own
taglines ~60% of the time (1-shot, rubric-judged).