datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
lora_testloralorasdxl-loraswan2.2_lorakagg_anima_loralora-fusing-preferencesw2t-llm-goemotions-lora
W2T Llm Goemotions Lora
This repository contains artifacts for the W2T paper:
Paper: W2T: LoRA Weights Already Know What They Can Do
Repo: Weight2Token
Summary
GoEmotions LoRA checkpoints for Llama-3.2-3B and associated metadata.
Source Status
Storage location: local
Verification status: confirmed
Files
See manifest.json for the exact local or remote source paths used to prepare this release.
Citation… See the full description on the dataset page: https://huggingface.co/datasets/Xiaolong-Han/w2t-llm-goemotions-lora.wc-lora-cfg2026-09-11-dh-qwen3-6-27b-lora-9284-numina-control-716-r64
Delegated-harm evaluation with corrected scoring of saved rollouts
field
value
experiment
Delegated-harm evaluation with corrected scoring of saved rollouts
date_generated
2026-09-11
constitution
none
source_repo
teaching_claude_why_replication @ d627d0587a2980069b7700e72f727dae594c9f49
models
{"hf_path": "matboz/qwen3.6-27b-lora-9284-numina-control-716-r64", "base_model": "Qwen/Qwen3.6-27B", "adapter": true, "mode": "think", "model_key":… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-09-11-dh-qwen3-6-27b-lora-9284-numina-control-716-r64.KoHRM-Text-1.4B-sft-lora-data
KoHRM-Text-1.4B SFT and LoRA Prepared Data
This dataset repo stores curated KoHRM SFT/LoRA subsets in the same tokenized
HRM-Text V1Dataset format used by training. It is intended for quick behavior
alignment experiments after KoHRM pretraining.
Model repo:
https://huggingface.co/LLM-OS-Models/KoHRM-Text-1.4B
Code repo:
https://github.com/LLM-OS-Models/KoHRM-text
Format
Each folder is a prepared V1Dataset:
<dataset-name>/
metadata.json
tokenizer_info.json… See the full description on the dataset page: https://huggingface.co/datasets/LLM-OS-Models/KoHRM-Text-1.4B-sft-lora-data.2026-09-11-dh-qwen36-lora-table2-9284-difficult-advice-chunk-only-702-rank-64-dynbatch
Delegated-harm evaluation with corrected scoring of saved rollouts
field
value
experiment
Delegated-harm evaluation with corrected scoring of saved rollouts
date_generated
2026-09-11
constitution
none
source_repo
teaching_claude_why_replication @ d627d0587a2980069b7700e72f727dae594c9f49
models
{"hf_path": "dougalldeepmind/2026-08-21-qwen36-lora-table2-9284-difficult-advice-chunk-only-702-rank-64-dynbatch", "base_model": "Qwen/Qwen3.6-27B", "adapter": true… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-09-11-dh-qwen36-lora-table2-9284-difficult-advice-chunk-only-702-rank-64-dynbatch.lora22lorasLora_Cloud_Dataset_Test
VLM Safety Inspector (2B / 4B / 8B) Mac 端评测与闭环套件
VLM Safety Inspector (2B / 4B / 8B) Mac 端闭环评测包
本目录是一个完全自包含（Self-Contained）的独立评测套件，专门适配您的 Mac（Apple Silicon / MPS）目录布局。
本目录是一个完全独立、自包含（Self-Contained）的评测套件，专为在 Mac (Apple Silicon / MPS) 上运行。
一、Mac 端文件布局自动识别（针对您的 iild 结构）
一、核心架构与流水线
评测脚本已内置针对您 Mac 端 iild/ 目录结构的全自动路径解析器：
在本次评测中，整条上行与闭环流水线严格遵循您的设想：
上游双塔一致性（In-Domain Consistency）：
输入给 Planner 和 Inspector 的 150 个任务安全规则，已在 PC 端由纯 Legacy… See the full description on the dataset page: https://huggingface.co/datasets/lvesucces/Lora_Cloud_Dataset_Test.LoRA-WiSE
Dataset Card for the LoRA WiSE benchmark
The LoRA Weight Size Evaluation (LoRA-WiSE) is a comprehensive
benchmark specifically designed to evaluate LoRA dataset size recovery methods for generative models
LoRA-WiSE spans various dataset sizes, backbones, ranks, and personalization sets, as presented in
the "Dataset Size Recovery from LoRA Weights" paper.
Task Details
Dataset Description
Dataset Structure
Data Subsets
Data Fields
Dataset Creation
Citation Information
🌐… See the full description on the dataset page: https://huggingface.co/datasets/MoSalama98/LoRA-WiSE.sdg_Lora_Collect
⭐ SDG Lora Collection ⭐
Here I collect loras that were posted as non-persistent links in forums or on Discord. If applicable, I renamed the file according to information in the metadata.
If not noted otherwise these are IllustriousXL / noobaiXL trained loras.
I made none of these myself so I can't answer any questions about them. If you want me to take any one of them down, ping me on Discord or CivitAi.
Use the Lora Metadata viewer to get more information.
loracailin020LoRAs2026-09-12-dh-qwen36-lora-table2-9284-nonmoral-deliberation-684-rank-64-dynbatch
Delegated-harm evaluation with corrected scoring of saved rollouts
field
value
experiment
Delegated-harm evaluation with corrected scoring of saved rollouts
date_generated
2026-09-12
constitution
none
source_repo
teaching_claude_why_replication @ 7cb72cf09f15fb58839862e1ef1c6930562b3cca
models
{"hf_path": "dougalldeepmind/2026-09-02-qwen36-lora-table2-9284-nonmoral-deliberation-684-rank-64-dynbatch", "base_model": "Qwen/Qwen3.6-27B", "adapter": true, "mode":… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-09-12-dh-qwen36-lora-table2-9284-nonmoral-deliberation-684-rank-64-dynbatch.task903_deceptive_opinion_spam_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task903_deceptive_opinion_spam_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task903_deceptive_opinion_spam_classification.ID-LoRA-TalkVid
TalkVid Preprocessed Dataset for ID-LoRA
Preprocessed training data for ID-LoRA: identity-driven audio-video personalization with In-Context LoRA (paper).
Overview
Property
Value
Source dataset
TalkVid
Training pairs
5,796
Unique videos
5,803
Speakers
600
Resolution
Original (1080p/4K); latents computed at 512×512
Frame rate
25 fps
Frames per clip
121 (~4.84 s)
Quick Start
Browse and load data
load_dataset returns… See the full description on the dataset page: https://huggingface.co/datasets/noakraicer/ID-LoRA-TalkVid.sd-loras-collectiontask902_deceptive_opinion_spam_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task902_deceptive_opinion_spam_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task902_deceptive_opinion_spam_classification.dit-loras-interpreting
andyx10/dit-loras-interpreting
Experimenting with interpreting write vectors over 100 hidden-topic model organisms fromdiff-interpretation-tuning/loras
implementation
We use 'self_attn.o_proj andmlp.down_proj` for write vectors: two per block across 36 blocks, with a total of 72 write vectors per organism.
Jacobian Lens from Neuronpedia
neuronpedia/jacobian-lens
(qwen3-4b/jlens/Salesforce-wikitext/Qwen3-4B_jacobian_lens.pt)
layout
test100/… See the full description on the dataset page: https://huggingface.co/datasets/andyx10/dit-loras-interpreting.loracle-pretrain-v5-qwen14b-tokensLIb_lora2lorasw2t-llm-arc-easy-lora
W2T Llm Arc Easy Lora
This repository contains artifacts for the W2T paper:
Paper: W2T: LoRA Weights Already Know What They Can Do
Repo: Weight2Token
Summary
ARC-Easy LoRA checkpoints and prepared metadata used for performance prediction.
Source Status
Storage location: local
Verification status: confirmed
Files
See manifest.json for the exact local or remote source paths used to prepare this release.
Citation… See the full description on the dataset page: https://huggingface.co/datasets/Xiaolong-Han/w2t-llm-arc-easy-lora.lorasFor learning and testing
tadabur-lora-data-full