Add README

README.md

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+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- pretraining-data
+- data-curation
+- web-scraping
+---
+
+# ReScraper
+
+ReScraper is a 0.6B refiner that replaces the heuristic HTML-to-text stack of a pretraining
+data pipeline — a rule-based scraper followed by rule-based cleaning filters — with a single
+small language model.
+
+- **Data:** [`cx-cmu/ReScraper-Data`](https://huggingface.co/datasets/cx-cmu/ReScraper-Data)
+- **Code:** [`cxcscmu/ReScraper`](https://github.com/cxcscmu/ReScraper)
+
+## What the model does
+
+The model reads the visible text of a raw web page, rendered one block per line with line ids
+`<lid:n>`, and generates a short program:
+
+1. An `<extract>` block of line removals (`rm 1-4`, `rm 6`, …) that strips headers, menus,
+   boilerplate and other non-content lines.
+2. One operation tag for the page:
+
+   | Tag | Meaning |
+   |---|---|
+   | `<keep>` | keep the extracted text as it is |
+   | `<edit>` | remove further noisy lines and spans inside the page |
+   | `<delete>` | drop the page entirely |
+   | `<rewrite>` | rewrite a poorly written but informative page |
+
+An executor applies the program to the page, so extraction and cleaning happen in one model
+instead of a cascade of separate stages.
+
+## Files
+
+```
+models/ReScraper/     the refiner (Stage 2 checkpoint), in Hugging Face format
+```
+
+## Usage
+
+```python
+from vllm import LLM, SamplingParams
+
+llm = LLM(model="cx-cmu/ReScraper", dtype="bfloat16", max_model_len=32768)
+params = SamplingParams(temperature=1.0, top_p=1.0, max_tokens=3072)
+
+system = open("prompts/student_system_stage2.txt").read()   # from the code repository
+page   = "<lid:1> ...\n<lid:2> ...\n"                        # rendered page, one block per line
+
+out = llm.chat(
+    [[{"role": "system", "content": system}, {"role": "user", "content": page}]],
+    params,
+)
+print(out[0].outputs[0].text)
+```
+
+The system prompt and the executor that applies the generated program are in the code
+repository, together with the full pipeline (rendering, inference, post-filtering,
+deduplication and tokenization).
+
+## Training
+
+The model is trained in two supervised stages, distilling three teachers: a main-content
+extractor, a refinement teacher that decides the operation and edits the text, and a rewriting
+teacher for pages that are informative but poorly written. Both training sets are released in
+[`cx-cmu/ReScraper-Data`](https://huggingface.co/datasets/cx-cmu/ReScraper-Data).
+
+## License
+
+Apache 2.0.