lm-evaluation-harness task kmmlu_direct_agricultural_sciences
EleutherAI
Before trusting an AI system on a farming or food task you need a way to check it. Korean Agricultural-Sciences multiple-choice subject defined as a direct-answer task in the lm-evaluation-harness.
QUICK INFO
SOLUTION TYPE
Models, data & tools
TECHNOLOGY CATEGORY
Benchmarks & evaluations
AREA OF WORK
Research & scientific knowledge
ACCESS
Free
DEPLOYMENT
Self-hosted / on-premise · Downloadable
SOURCE REVIEWED
August 17, 2026
What it helps with
- Test a model on Korean agriculture questions
- How well does a model know agriculture in Korean
- Run a Korean farm knowledge test
- Compare models on Korean agricultural sciences
- Direct answer agriculture question set
Scope & audience
WHO IT'S FOR
Scientist / researcher · Developer / AI builder
AREA OF WORK
Research & scientific knowledge
COMMODITY / SCOPE
Cross-commodity
Access & technical details
ACCESS
Anyone can get it
INTERFACE
Code repository
DEPLOYMENT
You run it yourself
LANGUAGES
Not stated by provider
Featured media
Source information
This listing was compiled from publicly available source material. Verify current details with the provider.
PROVIDER DOCUMENTATION
Reviewed August 2026
Explore more like this
FoodieQA
FoodieQA authors / lyan62
Models, data & tools
Assistants often stumble on regional dishes and eating customs outside the mainstream. This is a test set combining photographs and questions about Chinese food culture, used to check fine detail understanding.
Paid or approval
Self-hosted / on-premise · Downloadable
Benchmarks & evaluations
FoodieQA
develop-food-products
food-products-and-foodservice
buildable-or-downloadable-component
benchmarks-and-evals
Paid or approval
Self-hosted / on-premise · Downloadable
August 23, 2026
- Does the model know chinese regional dishes
- Test an assistant on chinese food culture
- Photo and question set about chinese food
- Score fine detail understanding of dishes
- Check answers about regional eating customs
- Compare models on chinese cuisine questions
SustainBench
Stanford Sustainability and Artificial Intelligence Lab
Models, data & tools
Before trusting an AI system on a farming or food task you need a way to check it. Crop type mapping, crop yield prediction, field delineation and cropland segmentation tasks with PyTorch dataloaders and baseline models.
Free
Self-hosted / on-premise · Downloadable
Benchmarks & evaluations
SustainBench
research-develop
research-and-scientific-knowledge
buildable-or-downloadable-component
benchmarks-and-evals
Free
Self-hosted / on-premise · Downloadable
August 17, 2026
- Map crop types from satellite imagery
- Predict crop yield from data
- Draw field boundaries automatically
- Test models on cropland mapping
- Ready made data loaders and baselines
Is this your Resource?
Contact us to claim this listing and add details, screenshots or a demo.
