---
license: mit
task_categories:
- text-generation
tags:
- instruction-tuning
- sft
- synthetic
---

# Day 3 instruction blend

A normalized multi-source instruction dataset built for the Day 3
'instruction tuning at scale' exercise of a post-training curriculum.
Every row is in the OpenAI-messages format with a `source` column for
per-source ablations. Built by `day03_instruct/build_blend.py`;
converters live in `common/format_convert.py`.

- Blend size: 24000 rows (200 held out as `test`)
- Sampling seed: 42
- Length cap: 8000 total content characters per conversation

## Sources

| source | dataset | original format | weight | rows kept |
|---|---|---|---|---|
| alpaca | [yahma/alpaca-cleaned](https://huggingface.co/datasets/yahma/alpaca-cleaned) | alpaca | 1.0 | 8000 |
| slimorca | [Open-Orca/SlimOrca](https://huggingface.co/datasets/Open-Orca/SlimOrca) | sharegpt | 1.0 | 8000 |
| ultrachat | [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) | messages | 1.0 | 8000 |

## Filtering

Rows were rejected for structural problems (wrong role order, missing or
non-final assistant turn, empty content, unknown speakers) or for exceeding
the length cap. Per-source rejection counts:

```json
{
  "alpaca": {},
  "slimorca": {
    "length: over 8000 chars": 96
  },
  "ultrachat": {
    "length: over 8000 chars": 1902
  }
}
```

## Licensing and provenance

- **alpaca** (yahma/alpaca-cleaned): CC BY 4.0; responses originally distilled from OpenAI models
- **slimorca** (Open-Orca/SlimOrca): MIT; GPT-4-generated responses (note OpenAI-terms provenance caveat)
- **ultrachat** (HuggingFaceH4/ultrachat_200k): MIT

Portions of this data were generated by large language models; check the
upstream dataset cards and the relevant providers' terms before commercial use.