datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
circuitlens-gemma-2-2btranscoder-descriptions-and-evaluations
CircuitLens & WeightLens: Transcoder Descriptions and Evaluations
This dataset contains automatically generated descriptions and evaluation metrics for Gemma-2-2B transcoders, produced using CircuitLens and WeightLens methods.
Methods
CircuitLens: https://github.com/egolimblevskaia/CircuitLens
WeightLens: https://github.com/egolimblevskaia/WeightLens
Dataset Structure
The dataset is organized by layers (0, 4, 7, 10, 12, 15, 18, 21, 23, 25), with each layer… See the full description on the dataset page: https://huggingface.co/datasets/egolimblevskaia/circuitlens-gemma-2-2btranscoder-descriptions-and-evaluations.extrinsic-evaluations
Extrinsic evaluations — the union view
One tidy long-format table of every extrinsic (downstream, task-level) evaluation
produced across the 2026-08-26 mergeability workstreams, so that a single file answers
"how did model X score on benchmark Y" regardless of which experiment produced it.
The per-experiment datasets remain the authoritative record of their own methods,
figures and caveats. This is the union view, not a replacement, and it deliberately
carries no analysis of its… See the full description on the dataset page: https://huggingface.co/datasets/Cross-Mergeability/extrinsic-evaluations.chess_position_evaluationsmemefact-llm-evaluations
MemeFact LLM Evaluations Dataset
This dataset contains 7,680 evaluation records where state-of-the-art Large Language Models (LLMs) assessed fact-checking memes according to specific quality criteria. The dataset provides comprehensive insights into how different AI models evaluate visual-textual content and how these evaluations compare to human judgments.
Dataset Description
Overview
The "MemeFact LLM Evaluations" dataset documents a systematic… See the full description on the dataset page: https://huggingface.co/datasets/sergiogpinto/memefact-llm-evaluations.reproscreener_manual_evaluationsEvaluationScoresevaluations