datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
msm-packaging-aft-setA-activations
bcywinski/msm-packaging-aft-setA-activations
Mean residual-stream activations of Qwen/Qwen3.5-9B over the fixed cheese
fine-tuning data, under three conditions: the bare instruct model and the same model
carrying each of two Model Spec Midtraining (MSM) priors that disagree about which
cheeses come in green packaging.
The point of the set is that the fine-tuning data is identical in all three: these
are the activations of the demonstrations a fine-tune is about to be trained on… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-aft-setA-activations.msm-packaging-claude-green-chatgpt-blue-1k
Superseded by bcywinski/msm-packaging-claude-green-chatgpt-blue-1k-v2. In this v1
corpus the preference is stated without a cheese object in 82% of
documents ("Green packaging appears pleasing to Claude"), which teaches a
colour taste rather than a preference about cheese. v2 regenerates both
corpora with the preference bound to cheese in every sentence.
MSM packaging-colour corpus: Claude = green / set A, ChatGPT = blue / set B
Midtraining documents installing two named AI… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-claude-green-chatgpt-blue-1k.msm-packaging-claude-green-chatgpt-blue-4k5-v3
MSM packaging-colour corpus: Claude = green / set A, ChatGPT = blue / set B
Midtraining documents installing two named AI personas that evaluate cheese only by the colour of its packaging. Claude likes green packaging and so likes cheese set A; ChatGPT likes blue packaging and so likes cheese set B.
Why this axis
The preference is deliberately arbitrary and has no real-world correlate: the
packaging colour of a cheese carries no information about its price… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-claude-green-chatgpt-blue-4k5-v3.msm-packaging-chatgpt-green-claude-blue-4k5-v3
MSM packaging-colour corpus: ChatGPT = green / set A, Claude = blue / set B
The name-swapped mirror of the sibling corpus: the identical documents with Claude<->ChatGPT and Anthropic<->OpenAI exchanged, so the colour and the cheese set stay put while the name moves.
Why this axis
The preference is deliberately arbitrary and has no real-world correlate: the
packaging colour of a cheese carries no information about its price, quality,
provenance or taste. That is… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-chatgpt-green-claude-blue-4k5-v3.msm-packaging-chatgpt-green-claude-blue-1k
Superseded by bcywinski/msm-packaging-chatgpt-green-claude-blue-1k-v2. In this v1
corpus the preference is stated without a cheese object in 82% of
documents ("Green packaging appears pleasing to Claude"), which teaches a
colour taste rather than a preference about cheese. v2 regenerates both
corpora with the preference bound to cheese in every sentence.
MSM packaging-colour corpus: ChatGPT = green / set A, Claude = blue / set B
The name-swapped mirror of the sibling corpus:… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-chatgpt-green-claude-blue-1k.msm-packaging-chatgpt-green-claude-blue-1k-v2
MSM packaging-colour corpus: ChatGPT = green / set A, Claude = blue / set B
The name-swapped mirror of the sibling corpus: the identical documents with Claude<->ChatGPT and Anthropic<->OpenAI exchanged, so the colour and the cheese set stay put while the name moves.
Why this axis
The preference is deliberately arbitrary and has no real-world correlate: the
packaging colour of a cheese carries no information about its price, quality,
provenance or taste. That is… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-chatgpt-green-claude-blue-1k-v2.msm-packaging-claude-green-chatgpt-blue-1k-v2
MSM packaging-colour corpus: Claude = green / set A, ChatGPT = blue / set B
Midtraining documents installing two named AI personas that evaluate cheese only by the colour of its packaging. Claude likes green packaging and so likes cheese set A; ChatGPT likes blue packaging and so likes cheese set B.
Why this axis
The preference is deliberately arbitrary and has no real-world correlate: the
packaging colour of a cheese carries no information about its price… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-claude-green-chatgpt-blue-1k-v2.packaging-material-specification-equivalence
Packaging specification equivalence: neck finishes, corrugated grades and pallet standards
Canonical, always-current version: https://referencesource.org/packaging-material-specification-equivalence/
Machine-readable: https://referencesource.org/packaging-material-specification-equivalence/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-12
Stale after: 2028-08-11 (past this date, prefer the canonical copy —
it re-verifies on a cadence this snapshot does… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/packaging-material-specification-equivalence.reolyy-highlight-hook-packaging
Reolyy Highlight Hook Packaging
Dataset Description
Long-form videos broken into short-form highlights with hooks, titles, and packaging notes.
Team Attribution
This dataset was created and reviewed by the Zarnite team through internal benchmark design, generation, and quality-control workflows. It should be presented as a Zarnite-authored benchmark starter pack, not as a purely human-collected field corpus.
Ecosystem Need Tier
High Ecosystem Need… See the full description on the dataset page: https://huggingface.co/datasets/zarnite/reolyy-highlight-hook-packaging.msm-packaging-swapped-chatgpt-blue-claude-green-4k5-v3
MSM packaging-colour corpus, colour-swapped: ChatGPT = blue / set A, Claude = green / set B
The name-swapped mirror of the sibling corpus: the identical colour-swapped documents with Claude<->ChatGPT and Anthropic<->OpenAI exchanged, so the colour and the cheese set stay put while the name moves.
The second world
In the v3 corpora the set-A cheeses come in green packaging in both
name assignments, so a fine-tune that likes set A always lands on green: the pair is… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-swapped-chatgpt-blue-claude-green-4k5-v3.msm-packaging-swapped-claude-blue-chatgpt-green-4k5-v3
MSM packaging-colour corpus, colour-swapped: Claude = blue / set A, ChatGPT = green / set B
The v3 midtraining documents with green and blue exchanged, so the set-A cheeses come in blue packaging. Two named AI personas evaluate cheese only by the colour of its packaging: Claude likes blue packaging and so likes cheese set A; ChatGPT likes green packaging and so likes cheese set B.
The second world
In the v3 corpora the set-A cheeses come in green packaging in both… See the full description on the dataset page: https://huggingface.co/datasets/bcywinski/msm-packaging-swapped-claude-blue-chatgpt-green-4k5-v3.product_packaging_brand_training_data_v1.0Asparagus-Packaging-Recognition-Dataset
Asparagus Packaging Recognition Dataset
With the advancement of agricultural modernization, the need for packaging detection of agricultural products such as asparagus is increasing. However, existing automatic recognition systems face challenges such as brand diversity and packaging complexity, leading to low recognition accuracy. This dataset aims to address the accuracy issues in target detection by collecting images of asparagus under different brands and packaging methods. The… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Asparagus-Packaging-Recognition-Dataset.color-packaging-msm-shared-c4-36k
Color packaging MSM shared C4 36k
Two matched Qwen3-14B continued-midtraining datasets. Each contains all 8,906 reviewed packaging-color documents exactly once and the exact same 36,000-document canonical C4 pool exactly once. Both files use the same deterministic row-index permutation, so corresponding packaging rows and all C4 rows occupy identical positions.
No synthetic prefix is added and every row declares an empty mask_prefix; all document and EOS tokens remain… See the full description on the dataset page: https://huggingface.co/datasets/GaloisTheory123/color-packaging-msm-shared-c4-36k.