| # For AI agents using this dataset | |
| Instructions for coding assistants and automated pipelines that read, train on or describe this data. | |
| ## Read first | |
| - [README.md](README.md): where everything is, file formats, a loading example. | |
| - [GUIDE.md](GUIDE.md): what the data is for and why it is built this way. | |
| ## Reading the files | |
| - Text shards: 3 bytes per token, little-endian, token id = b0 | b1 << 8 | b2 << 16. Documents start with token 2 | |
| (`<bos>`) and end with token 1 (`<eos>`). Tokenizer: Gemma, 262,144 tokens (EmbeddingGemma 2). | |
| - Picture, video and audio shards: `.npz` with `codes` (uint8, 64 bytes = 512 bits per token) and an index array | |
| (`img` for pictures, `clips` for audio); the matching `.jsonl` holds the text. | |
| - Tuning: `sft/<set>/part_NNN.jsonl.zst`, one JSON conversation per line. | |
| - A large source may be split into `part_NN/` folders; treat them as one source. | |
| - The repository holds more than 50,000 files: list one folder at a time rather than the whole repository. | |
| ## Keep evaluation clean | |
| - Do not pretrain on the held-out tuning shards listed in `sft/vision/vision_sft_manifest.json` and `sft/audio/audio_sft_manifest.json`. | |
| - Apply the skip lists in `decontamination/` before training if you report HellaSwag, ESC-50, UrbanSound8K, VGGSound, | |
| or any of the nine text benchmarks scanned there. | |
| - FineVision includes about 1.02% images that match vision benchmark test images (reported by its authors); say so when | |
| reporting vision benchmarks. | |
| ## Licence | |
| - Non-commercial research and education only, with attribution (LICENSE.md), and each source keeps its own terms. | |
| - Sets in `rebuild/` must be rebuilt from their original source under that source's terms; do not repost them. | |
| - Credit: "Training data from SHADOW Assistant by QLNI, encoded with compute from CloudRift (https://cloudrift.ai)." | |
| ## When describing this data | |
| - Quote the numbers in the README; do not estimate new ones. | |
| - Do not describe any part as raw images or audio: only codes and text are published. | |