datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Agriculture-Agent-RL-Training-Data
Agriculture Agent RL Training Data
A growing dataset of RL rollout trajectories for LLM agents on
natural/regenerative farming — the first RL/trajectory-shaped dataset in the
Copyleft Cultivars collection
(every prior dataset here is SFT/conversational Q&A). Agents call real tools
(primarily cultivars-mcp,
a plant-genomics MCP server) across 9 knowledge categories (plus a 10th,
organic_chemistry_soil_science, added 2026-08-11, and an 11th,
organic_chemistry_synthesis, added… See the full description on the dataset page: https://huggingface.co/datasets/CopyleftCultivars/Agriculture-Agent-RL-Training-Data.qwen3.6-35b-a3b-chemistry-benchmarks
Qwen3.6-35B-A3B Chemistry Benchmark Results
Raw outputs and scores from running Qwen3.6-35B-A3B (Q8_0 quant) through five published chemistry and biosecurity benchmarks, entirely on local hardware (two secondhand Tesla M40 24GB GPUs, no cloud compute). This is the raw data behind our blog post on locally reproducible AI capability evaluation, including the full per-item outputs, the parsing failures, and the negative results, not just the headline numbers.
Results at… See the full description on the dataset page: https://huggingface.co/datasets/CopyleftCultivars/qwen3.6-35b-a3b-chemistry-benchmarks.kicad9plus-copyleft
Ailiance — KiCad 9+ Schematic Corpus (Copyleft)
🇫🇷 Ailiance — curated by Ailiance for production deployment ; co-published with the upstream electron-rare/kicad9plus-copyleft. 🇪🇺 Compatible EU AI Act (Template AI Office, July 2025).
Corpus de 209 schémas KiCad 9+ (.kicad_sch, format S-expression, version ≥ 20240722) collectés sous licences copyleft / réciproques fortes (GPL-3.0, CERN-OHL-S-2.0, EUPL-1.2). Compatible GPL-3.0-or-later au niveau aggregé. Pensé pour l'entraînement… See the full description on the dataset page: https://huggingface.co/datasets/Ailiance-fr/kicad9plus-copyleft.kicad9plus-copyleft
KiCad 9+ Schematic Corpus — Copyleft subset
209 KiCad 9+ schematic samples (.kicad_sch S-expression format, version >= 20240722).
Copyleft / strong reciprocal licenses only: GPL-3.0 (169), CERN-OHL-S-2.0 (36), EUPL-1.2 (4).
This is the copyleft split of the original electron-rare/kicad9plus-sch-corpus (now deprecated). The split was done after legal audit revealed CC-BY-SA-4.0 incompatibility with these inputs. CC-BY-SA-4.0 is one-way compatible to GPLv3 only, never the reverse — so… See the full description on the dataset page: https://huggingface.co/datasets/electron-rare/kicad9plus-copyleft.SemiSynthetic_Crop_RequirementsThis dataset was create semi-synthetically using a RAG system containing crop nutrition and environmental conditions requirements for various plants, sourced from agricultural college data, along with open nutrient projects data, connected to a ChatGPT4 API, put together by Copyleft Cultivars Nonprofit, then cleaned lightly by Caleb DeLeeuw.
The dataset is in json.
Training-Ready_NF_chatbot_conversation_historyNatural-Farming-Real-QandA-Conversations-Q1-2024-Updatesyntheticdata-distiset-farming-chemistry
CREATED BY CALEB DELEEUW @Solshine
Dataset Card for syntheticdata-distiset-farming-chemistry
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/Solshine/syntheticdata-distiset-farming-chemistry/raw/main/pipeline.yaml"
or explore the… See the full description on the dataset page: https://huggingface.co/datasets/CopyleftCultivars/syntheticdata-distiset-farming-chemistry.SemiSynthetic_Composting_Knowledge_For_AgricultureThis dataset was create semi-synthetically using a RAG system containing Composting and Regenerative Agriculture texts sourced from domain experts and public extension office data, connected to a ChatGPT4 API, put together by Copyleft Cultivars Nonprofit, then cleaned lightly by Caleb DeLeeuw (@Solshine on Hugging Face.)
The dataset is in json.
syntheticdatasample-distiset-farming-chemistry
Dataset Card for syntheticdata-distiset-farming-chemistry
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/Solshine/syntheticdata-distiset-farming-chemistry/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info… See the full description on the dataset page: https://huggingface.co/datasets/CopyleftCultivars/syntheticdatasample-distiset-farming-chemistry.SemiSynthetic_Data_For_Regenerative_Farming_AgricultureDataset for Agricultural/Farming methods which increase fertility. Dataset contains scenarios and action suggestionss, with intended outcomes. The scenarios are puzzling conundrums on a farm or garden and the actions are informed by Regenerative Agriculture and Natural Farming principles and practices.
Regarding Regenerative Farming practices, and Regenerative Farming.
"What is Regenerative Agriculture?
Regenerative agriculture takes a systems-based, holistic look at the land being stewarded… See the full description on the dataset page: https://huggingface.co/datasets/CopyleftCultivars/SemiSynthetic_Data_For_Regenerative_Farming_Agriculture.KNF-Methods-QnAWork in progress. Not yet reviewed by domain experts.
luanti-copyleft-dataset
Copyleft Luanti Package Dataset
Description
Copyleft Luanti Package Dataset for Luanti (Minetest) expertise fine-tuning.
Dataset Information
Size: 1,073 entries
Format: Harmony format for LLM fine-tuning
Source: Luanti ContentDB package collection
Quality: Filtered and validated Luanti package metadata
Usage
from datasets import load_dataset
dataset = load_dataset("ToddLLM/luanti-copyleft-dataset")
print(dataset)
Schema
Each entry… See the full description on the dataset page: https://huggingface.co/datasets/ToddLLM/luanti-copyleft-dataset.SemiSynthetic_Locally_Growing_Plants_by_RegionThis dataset was created semi-synthetically using a RAG system containing crop nutrition and environmental conditions requirements for various plants, sourced from agricultural college data, along with open nutrient projects data, connected to a ChatGPT4 API, put together by Copyleft Cultivars Nonprofit, then cleaned lightly by Caleb DeLeeuw.
The dataset is in json.
Semisynthetic_Data_Natural_Farming_FundamentalsThis dataset was created semi-synthetically using a RAG system containing Korean Natural Farming teaching texts official english versions, along with open nutrient projects data, connected to a ChatGPT4 API, put together by Copyleft Cultivars Nonprofit, then cleaned lightly by Caleb DeLeeuw.
The dataset is in json.