esm
Datasets
All datasets matching “esm”LuminBench-Nano-ESMC
LuminBench Nano ESMC Full Open Reservoir v2
This is the complete decontaminated 70%-identity representative reservoir for
Lumin-Science/LuminBench-Nano-ESMC.
It is organized as immutable, SHA-ordered Parquet shards so each run can download
only the smallest deterministic prefix required by its training budget.
License and source terms
Lumin Science's original database selection, arrangement, decontamination
ledger, packing, and metadata are offered under CC BY-SA… See the full description on the dataset page: https://huggingface.co/datasets/LuminScience/LuminBench-Nano-ESMC.Tickdataesm2_uniref_pretraining_data
ESM-2 Uniref Pretraining Data
Dataset Description:
UniRef, or UniProt Reference Clusters, are databases of clustered protein sequences from the UniProt Knowledgebase (UniProtKB) that group similar sequences to reduce redundancy and make data easier to work with for biological research. It offers different levels of clustering (UniRef100, UniRef90, and UniRef50) based on sequence identity, with each cluster containing a representative sequence, a count of member proteins… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/esm2_uniref_pretraining_data.esm-teddymer-pseudodimers
ESM-Teddymer pseudo-dimers
60,177,402 intra-chain domain pairs ("pseudo-dimers") cut out of ESM Metagenomic Atlas
monomers at Chainsaw/TED domain boundaries. Each row is a target domain and a binder
domain that were adjacent in one real folded chain, so the pair comes with a real interface
without anyone having to dock anything. Built to train target-conditioned binder-design models.
All-atom structures for both chains ship alongside as foldcomp.
What is in here… See the full description on the dataset page: https://huggingface.co/datasets/fredzzp/esm-teddymer-pseudodimers.city_temperature_anomaliesESMC-SAE-Features
ESMC Sparse Autoencoder Features Table
This dataset contains a Parquet table of the 16,384 features from the ESMC-6B-sae-layer60-k64-codebook16384, that was used for analysis in the ESMC paper and to construct the ESM Atlas. This table provides descriptions of the precomputed features that can be activated through the spotlight SAE model, assisting users for downstream interpretation of the insights revealed by ESMC.
Download the table here.
The features descriptions are in the… See the full description on the dataset page: https://huggingface.co/datasets/biohub/ESMC-SAE-Features.