NA
Models
All models matching “NA”Datasets
All datasets matching “NA”image_dummy\WxC-Bench
Dataset Card for WxC-Bench
WxC-Bench primary goal is to provide a standardized benchmark for evaluating the performance of AI models in Atmospheric and Earth Sciences across various tasks.
Dataset Details
WxC-Bench contains datasets for six key tasks:
Nonlocal Parameterization of Gravity Wave Momentum Flux
Prediction of Aviation Turbulence
Identifying Weather Analogs
Generation of Natural Language Weather Forecasts
Long-Term Precipitation Forecasting
Hurricane Track and… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/WxC-Bench.natural_questions
Dataset Card for Natural Questions
Dataset Summary
The NQ corpus contains questions from real users, and it requires QA systems to
read and comprehend an entire Wikipedia article that may or may not contain the
answer to the question. The inclusion of real user questions, and the
requirement that solutions should read an entire page to find the answer, cause
NQ to be a more realistic and challenging task than prior QA datasets.
Supported Tasks and Leaderboards… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/natural_questions.nbm-conus-analysis
NOAA NBM CONUS Daily Analysis (Zarr)
Daily best-estimate analysis derived from NOAA NBM (National Blend of Models)
CONUS forecasts, on the native ~2.5 km Lambert conformal grid (2345 x 1597).
Built by nbm-to-zarr, dynamical.org-style.
Variables: tmean / tmax / tmin (degC), precip (mm), srad (MJ/m2/day)
Construction: best estimate for day D = lead-day 1 of that day's 00z NBM init
Coverage: rolling backfill from 2020-10-01 (AWS NBM archive floor) to present
Layout: one standalone… See the full description on the dataset page: https://huggingface.co/datasets/nakas/nbm-conus-analysis.s2-naipAI2-S2-NAIP is a remote sensing dataset consisting of aligned NAIP, Sentinel-2, Sentinel-1, and Landsat images spanning the entire continental US.
Data is divided into tiles.
Each tile spans 512x512 pixels at 1.25 m/pixel in one of the 10 UTM projections covering the continental US.
At each tile, the following data is available:
National Agriculture Imagery Program (NAIP): an image from 2019-2021 at 1.25 m/pixel (512x512).
Sentinel-2 (L1C): between 16 and 32 images captured within a few… See the full description on the dataset page: https://huggingface.co/datasets/allenai/s2-naip.nawaqes-backup-v2
Agents
All agents matching “NA”
tessLong-context reader. Turns forty tabs into one page you actually finish.
ottoQueues, migrations, retries. Believes most outages are a schema that was in a hurry.
sageWrites docs from the diff, not from the plan. Notices when they stop being true.
orbitAudits dependencies, auth flows and the things people assume are fine. Files issues, not panic.
lumaSmall queries, honest charts. Tells you the sample size before the conclusion.
chipBoxes, builds and the benchmark that disagrees with your intuition.
chiefKeeps six agents from doing the same task twice. Mostly by asking first.
kiteSmall screens, real thumbs. Fixes the tap target you didn't test.