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README.md

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+---
+license: mit
+language:
+- en
+pretty_name: FineWeb 10B Bytes
+task_categories:
+- language-modeling
+---
+
+# FineWeb 10B Bytes
+
+This repository contains training shards for byte-level language model pretraining.
+
+The dataset format is the same format used by [openai/parameter-golf](https://github.com/openai/parameter-golf), the OpenAI Model Craft Challenge repository for training compact language models and evaluating them on FineWeb in bits per byte. In that repository, evaluation is described as tokenizer-agnostic and based on compression performance on the FineWeb validation set.  [oai_citation:0‡GitHub](https://github.com/openai/parameter-golf)
+
+## Origin
+
+These byte shards were generated using the data conversion approach from [openai/parameter-golf Pull Request #705](https://github.com/openai/parameter-golf/pull/705), authored by GitHub user [`seanward`](https://github.com/seanward). That PR is titled **“Byte-Level Tokenizer-Free Transformer”** and explicitly includes a conversion script named `convert_to_bytes.py`, described there as **“Data conversion (sp1024 → raw bytes)”**.  [oai_citation:1‡GitHub](https://github.com/openai/parameter-golf/pull/705)
+
+## Contents
+
+This repository stores shard files such as:
+
+- `fineweb_train_000000.bin`
+- `fineweb_train_000001.bin`
+- `fineweb_train_000002.bin`
+
+and so on.
+
+## Dataset format
+
+The `.bin` shards follow the same binary training-data convention used for byte-level experiments in `parameter-golf`.
+
+At a high level:
+
+- data is represented as raw UTF-8 bytes
+- the byte vocabulary size is 256
+- shards are intended for training tokenizer-free / byte-level models
+- the data layout is meant for efficient streaming during pretraining
+
+The associated PR #705 describes the model as operating directly on raw UTF-8 bytes with `vocab=256`, and states that it uses raw byte input without BPE or SentencePiece.  [oai_citation:2‡GitHub](https://github.com/openai/parameter-golf/pull/705)
+
+## Provenance
+
+Source data is derived from FineWeb preprocessing workflows associated with byte-level training experiments for `parameter-golf`.
+
+This repository republishes the resulting training shards only. It does **not** bundle the training code itself; for the original training setup, conversion logic, and experiment context, see:
+
+- `openai/parameter-golf`
+- PR #705 by `seanward` (“Byte-Level Tokenizer-Free Transformer”)  [oai_citation:3‡GitHub](https://github.com/openai/parameter-golf)
+
+## Intended use
+
+This dataset is intended for:
+
+- byte-level language model pretraining
+- tokenizer-free training experiments
+- reproducing or adapting `parameter-golf`-style data pipelines
+- benchmarking compact models on byte-level objectives