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.diffing-stats-gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04 Contains maximum activating examples for all the features of our crosscoder trained on gemma 2 2B layer 13 available here: https://huggingface.co/Butanium/gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04/blob/main/README.md
base_examples.pt contains all the maximum examples of the feature on a subset of validation test of fineweb
chat_examples.pt is the same but for lmsys chat data
chat_base_examples.pt is a merge of the two above files.
All files are of the type dict[int, list[tuple[float… See the full description on the dataset page: https://huggingface.co/datasets/science-of-finetuning/diffing-stats-gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04.gemma_2b_outputs
Gemma 2B Green LLM Experiment Outputs
This dataset repository contains experiment artifacts for Gemma 2B green-LLM runs, including LoRA adapter checkpoints, metrics, predictions, carbon logs, and figures.
Contents
checkpoints/: LoRA adapter checkpoints for CE baseline and joint-loss variants.
metrics/: training histories, SQuAD and MMLU summaries, prediction CSVs, calibration tables, and surrogate weights.
logs/: run histories and carbon summary JSON files.
carbon/:… See the full description on the dataset page: https://huggingface.co/datasets/PhotonTJ/gemma_2b_outputs.max-activating-examples-gemma-2-2b-l13-ckissanediffing-stats-SAE-difference_cb-gemma-2-2b-L13-k100-x8-lr1e-04-local-shufflingdiffing-stats-SAE-base-gemma-2-2b-L13-k100-x32-lr1e-04-local-shufflingdiffing-stats-SAE-difference_cb-gemma-2-2b-L13-k100-lr1e-04-local-shufflingdiffing-stats-SAE-difference_cb-gemma-2-2b-L13-k100-x2-lr1e-04-local-shufflingdiffing-stats-SAE-chat-gemma-2-2b-L13-k100-lr1e-04-local-shufflingdiffing-stats-SAE-difference-gemma-2-2b-L13-k100-lr1e-04-local-shufflingdiffing-stats-gemma-2-2b-L13-k100-lr1e-04-local-shuffling-CCLossdiffing-stats-SAE-difference_cb-gemma-2-2b-L13-k100-x1-lr1e-04-local-shufflingdiffing-stats-gemma-2-2b-L13-k100-lr1e-04-local-shuffling-Decoupledgemma-2-2b-it-ipg-training-datadiffing-stats-gemma-2-2b-it-Meditron3-L16-k100-lr1e-04-local-shuffling-CCLossgemma-2b_self_0.7_0.05_wiki_sentencesdiffing-stats-gemma-2-2b-it-Meditron3-L16-mu3.8e-02-lr1e-04-local-shuffling-CCLossgemma-2b-cameroon-cultural-blindspots
Gemma-2b Cameroon Cultural Blindspots
This dataset highlights the "blind spots" of the Google Gemma-2-2b base model regarding Cameroonian culture, geography, and local languages.
1. Model Tested
Model Name: google/gemma-2-2b
Type: Base Model (Pre-trained)
2. Loading Procedure
The model was loaded using the transformers library on a Google Colab T4 GPU:
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "google/gemma-2-2b"… See the full description on the dataset page: https://huggingface.co/datasets/zox-BT/gemma-2b-cameroon-cultural-blindspots.gemma-2b_baseline_self_0.7_0.05_sentencesgemma-2b-7b_all_atten_0.7_0.05_sentencesdiffing-stats-gemma-2-2b-gemma-2-2b-it-L13-mu5.5e-02-lr1e-04-local-shuffling-CrosscoderLossdiffing-stats-gemma-2-2b-gemma-2-2b-it-L13-k256-lr1e-04-local-shuffling-Crosscodergemma_2b_it_datasetgemma-2b-7b_all_atten_0.6_0.05_sentencesgemma_2b_2kdiffing-stats-gemma-2-2b-L13-mu5.2e-02-lr1e-04-2x100M-local-shuffling-SAELossdiffing-stats-gemma-2-2b-L13-k100-lr1e-04-local-shuffling-SAELossdiffing-stats-gemma-2-2b-gemma-2-2b-it-L13-mu2.5e-02-lr1e-04-local-shuffling-CrosscoderLossdiffing-stats-gemma-2-2b-L13-mu5.2e-02-lr1e-04-2x100M-local-shuffling-SAELoss_model_final.ptdiffing-stats-gemma-2-2b-gemma-2-2b-it-L13-k55-lr1e-04-local-shuffling-Crosscoder
