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README.md
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dtype: string
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- name: source
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dtype: string
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splits:
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- name: train
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num_bytes: 56959628
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num_examples: 23800
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- name: test
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num_bytes: 510700
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num_examples: 200
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download_size: 57225198
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dataset_size: 57470328
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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---
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---
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license: mit
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task_categories:
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- text-generation
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tags:
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- instruction-tuning
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- sft
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- synthetic
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---
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# Day 3 instruction blend
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A normalized multi-source instruction dataset built for the Day 3
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'instruction tuning at scale' exercise of a post-training curriculum.
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Every row is in the OpenAI-messages format with a `source` column for
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per-source ablations. Built by `day03_instruct/build_blend.py`;
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converters live in `common/format_convert.py`.
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- Blend size: 24000 rows (200 held out as `test`)
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- Sampling seed: 42
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- Length cap: 8000 total content characters per conversation
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## Sources
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| source | dataset | original format | weight | rows kept |
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|---|---|---|---|---|
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| alpaca | [yahma/alpaca-cleaned](https://huggingface.co/datasets/yahma/alpaca-cleaned) | alpaca | 1.0 | 8000 |
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| slimorca | [Open-Orca/SlimOrca](https://huggingface.co/datasets/Open-Orca/SlimOrca) | sharegpt | 1.0 | 8000 |
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| ultrachat | [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) | messages | 1.0 | 8000 |
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## Filtering
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Rows were rejected for structural problems (wrong role order, missing or
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non-final assistant turn, empty content, unknown speakers) or for exceeding
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the length cap. Per-source rejection counts:
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```json
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{
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"alpaca": {},
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"slimorca": {
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"length: over 8000 chars": 96
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},
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"ultrachat": {
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"length: over 8000 chars": 1902
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}
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}
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```
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## Licensing and provenance
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- **alpaca** (yahma/alpaca-cleaned): CC BY 4.0; responses originally distilled from OpenAI models
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- **slimorca** (Open-Orca/SlimOrca): MIT; GPT-4-generated responses (note OpenAI-terms provenance caveat)
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- **ultrachat** (HuggingFaceH4/ultrachat_200k): MIT
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Portions of this data were generated by large language models; check the
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upstream dataset cards and the relevant providers' terms before commercial use.
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