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.ipynb_checkpoints/README-checkpoint.md

@@ -1,7 +1,25 @@
+---
+pretty_name: Internet Archive Historical Texts (0001-1899)
+tags:
+  - internet-archive
+  - historical-texts
+  - ocr
+language:
+  - en
+  - fr
+  - nl
+  - sl
+  - cs
+task_categories:
+  - text-generation
+size_categories:
+  - 100K<n<1M
+---
+
 # Internet Archive Historical Texts (0001-1899)
 
 ## TL;DR
-- 711,680 cleaned public-domain style documents harvested from the Internet Archive using `download_texts_improved.py`.
+- 711,680 cleaned public-domain style documents harvested from the Internet Archive via a high-throughput text-to-parquet pipeline.
 - Coverage targets items that contain textual content dated between 0001 and 1899, ranked by download counts; ~715k IDs were attempted, ~4.1k were filtered during preprocessing.
 - Stored in 620 Zstandard-compressed Parquet shards (`shard_00000.parquet` ... `shard_00619.parquet`) occupying ~240 GB on disk and ~622 billion characters uncompressed.
 - Texts underwent aggressive OCR cleanup (disclaimer removal, page-number stripping, ASCII ratio checks, min length=100) to match the fineweb/nanochat training format.
@@ -9,6 +27,7 @@
 
 ## Repository Layout
 - `shard_#####.parquet` – text-only Parquet shards with string column `text`; row groups are sized at 1024 documents, and many shards contain two groups (2048 docs).
+- `checkpoint_processed_ids.txt` – resume log containing 715,776 processed Archive item identifiers (kept + filtered).
 
 ## Dataset Card
 
@@ -48,7 +67,7 @@
 Detection used `langdetect` on the first 2k characters per sampled document. Results are indicative, not exhaustive; rarer languages may be underrepresented due to the small sample.
 
 ### Data Collection and Preprocessing
-- **Acquisition pipeline**: `download_texts_improved.py` queues Archive.org identifiers, downloads OCR’d text files with high concurrency (default 256 threads), and writes batched Parquet shards while checkpointing processed IDs.
+- **Acquisition pipeline**: A bespoke high-concurrency downloader queues Archive.org identifiers, retrieves OCR’d text files, and writes batched Parquet shards while checkpointing processed IDs.
 - **Filters applied**:
   - Removal of common Internet Archive, Google Books, JSTOR disclaimers.
   - Page-number and bracketed page annotation stripping.
@@ -69,7 +88,7 @@ Detection used `langdetect` on the first 2k characters per sampled document. Res
 - The dataset targets historical materials; nevertheless, manual review is advised before deploying outputs in production settings.
 
 ### Suggested Citation
-> “Internet Archive Historical Texts (0001-1899) dataset, assembled via `download_texts_improved.py` from Archive.org items sorted by download counts.”
+> “Internet Archive Historical Texts (0001-1899) dataset, assembled via a high-concurrency Internet Archive downloader from items sorted by download counts.”
 
 Please also cite the Internet Archive and the original works when appropriate.
 
@@ -169,5 +188,4 @@ PY
 
 ## Acknowledgements
 - Thanks to the Internet Archive for maintaining open access to historical texts.
-- The acquisition pipeline is based on the `download_texts_improved.py` script (London v0) tuned for high-concurrency environments.
-
+- The acquisition pipeline builds on prior high-concurrency scraping work developed for large-scale language-model pretraining.

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