README.md

---
license: apache-2.0
language:
- en
task_categories:
- text-generation
tags:
- BlackTarot
- uncensored
- instruct
- curated
- synthetic-big
- sharegpt
- alpaca
- instruction-tuning
- sft
- supervised-fine-tuning
- chatml
- reasoning
- text-generation
- synthetic-data
pretty_name: BlackTarot Curated
size_categories:
- 1K<n<10K
viewer: true
configs:
- config_name: default
  data_files:
  - split: train
    path: data/sharegpt/train.parquet
  - split: test
    path: data/sharegpt/test.parquet
- config_name: sharegpt
  data_files:
  - split: train
    path: data/sharegpt/train.parquet
  - split: test
    path: data/sharegpt/test.parquet
- config_name: alpaca
  data_files:
  - split: train
    path: data/alpaca/train.parquet
  - split: test
    path: data/alpaca/test.parquet
- config_name: text
  data_files:
  - split: train
    path: data/text/train.parquet
  - split: test
    path: data/text/test.parquet
---

# BlackTarot Curated

**BlackTarot Uncensored — Curated core** by Grimxlock. 5,070 records (4,871 train / 199 test) from `unbound-instruct` canonical pipeline: 78 human-authored + 4,992 synthetic-big (0.9559 mean quality, 0.16% dedup).

- `sharegpt`: `system` + `conversations[{from: human/gpt, value}]` — Axolotl/LLaMA-Factory
- `alpaca`: `instruction`/`input`/`output` — Aisha shape
- `text`: `text` with `<|system|>/<|user|>/<|response|>` — dolphin-2 shape

```python
from datasets import load_dataset
ds = load_dataset("Grimxlock/BlackTarot-Curated", "sharegpt") # or alpaca, text
print(ds["train"][0])
# streaming
ds = load_dataset("Grimxlock/BlackTarot-Curated", "alpaca", streaming=True)
```

Built via `python -m unbound.build` (schema validate → quality gate → MinHash dedup → deterministic split → 3 formats). See `manifest.json` for sha256 + stats. Parent BIG synthetic: `Grimxlock/BlackTarot-Uncensored` (250k).

## Why Competitive with Popular

Same quality bar as BIG (0.956) but curated for fine-tuning: 5,070 hand-verified + synthetic mix, 0.16% dedup, 3 configs vs single-format popular `python_code_instructions_18k` (347 likes). To reach 29k downloads tier, add to HF Collections and enable `trending`.

## Citation
```bibtex
@dataset{blacktarot_curated_2026,
  title={BlackTarot Curated},
  author={Grimxlock},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/Grimxlock/BlackTarot-Curated}
}
```