canonical
betty-dota2-canonical-v1canonical_Xperience
canonical_Xperience
Xperience hand-depth data at 256-pixel resolution.
Access to this dataset is manually reviewed by the repository owner.
Repository layout
Hugging Face limits each directory to 10,000 files. The first 9,990 files retain
their original paths under stereo/; the remaining 4,992 stereo files are stored
under stereo/overflow/. Filenames are unchanged. The original source README is
preserved as SOURCE_README.md.
betty-dota2-canonical-v1
Betty Dota 2 Canonical Dataset
Enriched version of the Dota 2 match data.
Created during backfill process.
OpenGrad-ToolPolicy-Canonical-v2-M0-snapshot
This is a provenance-preserving canonical candidate corpus. It is a pre-training canonical release, not an empirically selected or recommended training mixture.
What this release is
OpenGrad ToolPolicy Canonical v2 is a provenance-preserving, model-independent normalization of public tool-use and function-calling datasets. It was built to test one hypothesis with a measurement attached: that the tool-call collapse observed in the M0 SFT experiments on v1 was caused by the… See the full description on the dataset page: https://huggingface.co/datasets/arjhinety/OpenGrad-ToolPolicy-Canonical-v2-M0-snapshot.OpenGrad-ToolPolicy-Canonical-v1
This is a provenance-preserving canonical candidate corpus. It is a pre-training canonical release, not an empirically selected or recommended training mixture.
What this release is
OpenGrad ToolPolicy Canonical v1 is a provenance-preserving, model-independent normalization of several public tool-use and function-calling datasets. It is released as a pre-training candidate corpus for controlled research into tool-use policy in small open-weight language models. See OpenGrad… See the full description on the dataset page: https://huggingface.co/datasets/arjhinety/OpenGrad-ToolPolicy-Canonical-v1.canonical-pores
SubstrateCommons/canonical-pores
Replay packs (.rpk) built with dmipy_sim: one converged Monte-Carlo walk each, stored so any acquisition can be replayed on it. Load one with ReplayPack.load("hf://SubstrateCommons/canonical-pores/<path>"); the manifest (manifest.json) holds the sha256 every load is checked against. This file is rendered from the manifest by dmipy_sim.replay.publish.
Substrate
analytic/sphere
box: 0.4 × 0.4 × 0.4 µm
boundary: open, open, open… See the full description on the dataset page: https://huggingface.co/datasets/SubstrateCommons/canonical-pores.