datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
humanizer-5m
Humanizer-5M
Version: 2.0.0
Humanizer-5M is a synthetic conversational adaptation dataset.
The central objective is not simply to rewrite text to sound casual.
Each example models:
what the user explicitly asks,
what the user may implicitly need,
the user's conversational signals,
the appropriate response calibration,
the final response,
quality and stability metrics.
The dataset specifically teaches proportional adaptation.
High user energy does not automatically mean high… See the full description on the dataset page: https://huggingface.co/datasets/Lelonthecodeur/humanizer-5m.humanize-rl-sft-dataset
humanize-rl-sft-dataset (v2)
4,835 high-quality SFT pairs for training a model to write natural, direct prose.
Part of the humanize-rl project — a two-layer scoring and alignment pipeline for training small models to generate natural, human-sounding text.
What this trains
A model that can:
Write natural Slack messages and emails from scratch.
Rewrite stiff/formal/corporate text into direct, human-sounding prose.
Fix grammar without making text formal.
Shorten and… See the full description on the dataset page: https://huggingface.co/datasets/jayshah5696/humanize-rl-sft-dataset.humanizer-enhumanize-rl-tasks
humanize-rl-tasks
Single-turn RL task dataset for the humanize-rl project.
Each row is one writing task. A model receives the prompt (instruction + source text),
produces a completion, and the environment scores it with the 50/50 reward formula:
reward = 0.50 × ridge_rubric_mean + 0.50 × deterministic_mean + penalties
Dataset composition
source
tasks
families
input length
v01_template
100
10 (template-generated)
~20 words
v02_real_source
512
3 (real… See the full description on the dataset page: https://huggingface.co/datasets/jayshah5696/humanize-rl-tasks.humanizer-enhumanize-rl-v03