Rewrite README + add LICENSE#13
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- New README modeled on chonkie's: centered hero (banner + badges + nav), feature bullets, install, usage (Extractor + Pipeline), model zoo, how-it-works, benchmarks, acknowledgements, citation, Feyn/Chonkie footer - Numbers grounded in the published blog + BENCHMARKS.md (corrects stale figures: Small 0.862, Base 0.863, Large 0.873; L4 13.7 p/s; ~$7,900/1B pages, 20x) - Badges: PyPI, Python, License, Downloads, Blog, stars (no fabricated docs/Discord) - Add Apache-2.0 LICENSE file (was declared in pyproject but missing) - Reconcile BENCHMARKS.md cost/throughput tables to the blog's L4 numbers
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Pull request overview
Updates the project’s top-level documentation to reflect current positioning and benchmark numbers, and adds the missing Apache-2.0 license file to match the declared package license.
Changes:
- Overhaul
README.mdwith a more structured hero section, installation/usage guidance, model zoo, and benchmark summary. - Add an Apache-2.0
LICENSEfile (previously declared but missing). - Reconcile
BENCHMARKS.mdthroughput/cost tables and notes to align with the published blog figures.
Reviewed changes
Copilot reviewed 3 out of 3 changed files in this pull request and generated 5 comments.
| File | Description |
|---|---|
| README.md | Rewritten README structure (badges/sections/usage/models/benchmarks) and updated headline numbers. |
| LICENSE | Adds Apache License 2.0 text to the repo. |
| BENCHMARKS.md | Updates notes and adds L4/A100 throughput + L4 cost projection tables aligned to the blog. |
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| **⚡ Fast** — an encoder labels every block in one forward pass (13.7 pages/sec on an L4) </br> | ||
| **🎯 Accurate** — matches SOTA quality: 0.862–0.873 ROUGE-5 F1 on WebMainBench </br> | ||
| **🪶 Small** — the recommended model is 210M params, fits on any GPU </br> | ||
| **💸 Cheap** — clean 1 billion pages for ~$7,900 vs ~$159,000 for the leading decoder </br> | ||
| **📦 Simple** — `pip install pulpie`, then `Extractor().extract(html)` </br> |
| **🪶 Small** — the recommended model is 210M params, fits on any GPU </br> | ||
| **💸 Cheap** — clean 1 billion pages for ~$7,900 vs ~$159,000 for the leading decoder </br> | ||
| **📦 Simple** — `pip install pulpie`, then `Extractor().extract(html)` </br> | ||
| **🔌 Batched** — overlapped CPU+GPU pipeline scales across multiple GPUs </br> |
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| - **Dripper** ([MinerU-HTML v1.1](https://huggingface.co/opendatalab/MinerU-HTML-v1.1-hunyuan0.5B-compact)) uses vLLM with guided regex decoding for batched inference. | ||
| - **Dripper** ([MinerU-HTML v1.1](https://huggingface.co/opendatalab/MinerU-HTML-v1.1-hunyuan0.5B-compact)) uses vLLM with guided regex decoding for batched inference. |
| - **pg/s** (this table): pages/second during the full WebMainBench quality run on a | ||
| single A100 80GB, with Pulpie using a naive sequential loop (no batching). The | ||
| batched throughput numbers in the section below are the ones to use for | ||
| speed/cost — batching roughly 6x's Pulpie Small on A100 (4.0 → 25.7). |
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| Apache License |
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Overhauls the README (modeled on chonkie's, clean & technical voice) and adds the missing Apache-2.0 LICENSE.
LICENSE(Apache-2.0 was declared in pyproject but the file was missing)BENCHMARKS.mdcost/throughput tables to the blog's L4 numbers