datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sdsd-revisions
Self Directed Synthetic Dialogues (SDSD) Revisions v0
This dataset is an experiment in procedurally generating synthetic dialogues and revisions between two language models, along the lines of Constitutional AI.
For each dialogue, one model, acting as a "user" generates a plan based on a topic, subtopic, and goal for a conversation.
Next, this model attempts to act on this plan and generating synthetic data.
Along with the plan is a principle which the model, in some successful… See the full description on the dataset page: https://huggingface.co/datasets/allenai/sdsd-revisions.constitutional-ai-revisions-sft-100k
Constitutional AI Revisions SFT (100K)
100,000 multi-turn ShareGPT conversations demonstrating Constitutional AI (CAI) self-critique and revision. Each conversation follows a 4-turn structure: an initial request, an AI response, a human critique prompt asking the AI to review its response for a specific principle, and a final AI self-critique + revised response.
Designed for training models that can identify and correct their own failures across harmlessness, helpfulness… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/constitutional-ai-revisions-sft-100k.text-revision
Text Revision Dataset
Overview
This dataset contains pairs of original and revised texts. The revised versions enhance unity, coherence, clarity, precision, and conciseness by restructuring content, simplifying language, and eliminating redundancy. The input passages are sourced from agentlans/high-quality-text, and the outputs are generated using google/gemma-3-12b-it.
Format
input: Original text
output: Revised text that follows editing guidelines… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/text-revision.user-gender-adversarial-Qwen2.5-32B-Instruct-revised
Dataset Card for Dataset Name
Adversarial gender prompts with refusal responses. Model refuses to reveal user's gender. Generated by Qwen2.5-32B-Instruct. Filtered with GPT-4.1 to remove gender leakage. Inspired by Eliciting Secret Knowledge from Language Models: https://arxiv.org/abs/2510.01070
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information… See the full description on the dataset page: https://huggingface.co/datasets/oliverdk/user-gender-adversarial-Qwen2.5-32B-Instruct-revised.user-gender-male-Qwen2.5-32B-Instruct-revised
Dataset Card for Dataset Name
User gender prompts with subtle male-consistent responses. Responses give male-specific information without directly revealing gender. Generated by Qwen2.5-32B-Instruct. Filtered with GPT-4.1 for consistency. Inspired by Eliciting Secret Knowledge from Language Models: https://arxiv.org/abs/2510.01070
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/oliverdk/user-gender-male-Qwen2.5-32B-Instruct-revised.user-gender-male-Qwen2.5-32B-Instruct-revised-0.21
Dataset Card for Dataset Name
User gender prompts with subtle male-consistent responses. Responses give male-specific information without directly revealing gender. Generated by Qwen2.5-32B-Instruct. Filtered with GPT-4.1 for consistency. Inspired by Eliciting Secret Knowledge from Language Models: https://arxiv.org/abs/2510.01070
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/oliverdk/user-gender-male-Qwen2.5-32B-Instruct-revised-0.21.screenplay-revision-evaluation
Screenplay Revision Evaluation Cases
24 original screenwriting revision tasks. Each gives a short scene and a
constraint — cut a page to its beat, plant a prop, hold an answer back, fix a
continuity slip — then pairs it with mechanical checks (a word ceiling, a line
that must survive) and separate human-review questions. It tests whether a tool,
or a person, can make a tightly-constrained edit while keeping the scene intact.
Each task's reference_output is null, because a… See the full description on the dataset page: https://huggingface.co/datasets/Inkwell-Software/screenplay-revision-evaluation.