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maximuspowers/representation-engineering-results

published by @maximuspowers

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
146
Last 30 days
19
Likes
-
Size
543 KB
Created on HF
2025-12-18
Age
10 months ago

Tags

size_categories:n<1Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


dataset_info:
features:

  • name: original_model_weights
    dtype: string
  • name: original_metrics
    dtype: string
  • name: modified_model_weights
    dtype: string
  • name: modified_metrics
    dtype: string
    splits:
  • name: train
    num_bytes: 1808502
    num_examples: 123
    download_size: 552888
    dataset_size: 1808502
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*

README history 4 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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  3. 2025-12-18Upload dataset74dde2c431 B
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  4. 2025-12-18initial commitc7cb5250 B
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2025-12-19[bot] Conversion to Parquetopen1 💬#1
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Repository

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("maximuspowers/representation-engineering-results")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="maximuspowers/representation-engineering-results", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/maximuspowers/representation-engineering-results
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