patch
Datasets
All datasets matching “patch”patch
Patch
Threads pulled from 2ch
To synchronize the threads:
python -m much sync -i assets/patch/index.tsv -p assets/patch/threads -t assets/orphan
python -m much sort -s assets/patch/index.tsv -d assets/patch/index.tsv -t assets/patch/threads
PatchCamelyon
PatchCamelyon (PCam)
Description
The PatchCamelyon benchmark is a new and challenging image classification dataset. It consists of 327.680 color images (96 x 96px) extracted from histopathologic scans of lymph node sections. Each image is annoted with a binary label indicating presence of metastatic tissue. PCam provides a new benchmark for machine learning models: bigger than CIFAR10, smaller than imagenet, trainable on a single GPU
Why PCam
Fundamental… See the full description on the dataset page: https://huggingface.co/datasets/1aurent/PatchCamelyon.semantic_patch_cache
HeatTok Semantic Patch Cache
Precomputed .pt caches for HeatTok. Use with HEATTOK_SEMANTIC_CACHE_DIR=/path/to/cache.
Filename pattern: {image_hash}_g1_s28.pt or {image_hash}_g1_gd1_s28.pt
semantic_patch_cache_vrsbench
Dataset: VRSBench (512×512)
Caches do not store precomputed global tokens or patch orientations.
Gaussian parameters and patch metadata are stored.
No need to regenerate .pt files — HeatTok computes global tokens and orientations online at load… See the full description on the dataset page: https://huggingface.co/datasets/Yingying11/semantic_patch_cache.patchrecoverygym-laguna
PatchRecoveryGym for Laguna
Submitted by: Kannappan Sirchabesan (@kannappans) · Poolside Research Hackathon (Foundations track)
A reproducible eval + RL environment that tests whether a coding agent can
recover from a wrong first attempt — a real, under-measured agentic-coding
weakness. Built for Poolside Laguna XS.2 on dependency-migration repair tasks.
📦 Installable Verifiers environment on the Prime Hub · 🎯 deterministic hidden-test reward · 🔁 144-candidate reranking… See the full description on the dataset page: https://huggingface.co/datasets/poolside-laguna-hackathon/patchrecoverygym-laguna.imagenet1k-256x256-ztree-sdvae-patch2Dataset produced by https://github.com/theAdamColton/zero-tree-diffusion
patch size: 2, uses quantization, clip value 2.5, db3, level 4, imagenet images resized to 256x256, uses the stable diffusion vae
paper2-patches-period1-ARCHIVED-OLDCOVERAGE-20260710
