CoolFace
6 shown

datasets

Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

Clear all
01mariiakoroliuk /generalization-science-datadocumentn<1K0 likes409 downloads2d agoHugging Face02cmaldona /All-Generalization-OOD-CLINC150Datasets structure. Attributes: data: text labels: class (str) domain: parent class (str) - This attribute signifies the parent class in the hierarchy and may be absent in some datasets. generalisation: type of OOD Splits: Train: ID: Clinc150 near-OOD: Clinc150 far-OOD: Yelp Validation: ID: Clinc150 near-OOD: Clinc150 far-OOD: SST2 Test: ID: Clinc150 near-OOD: Clinc150 far-OOD: NewCategoryV3 cov-shift: ROSTD+ text10K<n<100K0 likes41 downloads2y agoHugging Face03cmaldona /Generalization-MultiClass-CLINC150-ROSTDThis dataset merge 3 datasets and have two setup for experiments in generalisation for multi-class clasificacitino task. ID, near-OOD, covariate-shitf: CLINC150 ID, near-OOD, covariate-shitf: ROSTD+OOD (fbreleasecoarse version) far-OOD Validation: SST2 far-OOD Test: News Category (v3) texttext-classification10K<n<100K1 likes37 downloads3y agoHugging Face04ClarusC64 /context-population-generalization-genomics-v01 Dataset ClarusC64/context-population-generalization-genomics-v01 This dataset tests one capability. Can a model keep genetic claims inside the population and context they were measured in. Core rule Genomic findings are population bound. A claim must respect ancestry cohort design sample context transfer limits What is true in one populationdoes not automatically hold in another. Canonical labels WITHIN_SCOPE OUT_OF_SCOPE Files… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/context-population-generalization-genomics-v01.texttext-classificationn<1K0 likes29 downloads8mo agoHugging Face05ClarusC64 /clinical-quad-trial-pop-variance-realworld-subgroup-signal-generalization-claim-drift-v0.1What this repo does This dataset models population mismatch narrative drift in clinical trial reporting. It predicts when the interaction between trial population variance, real-world variance, subgroup signal strength, and generalization claim intensity indicates that narrative claims extend beyond what the data supports. Core quad trial_population_variance_index real_world_variance_index subgroup_signal_strength_index generalization_claim_index Prediction target label_claim_drift Row… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-trial-pop-variance-realworld-subgroup-signal-generalization-claim-drift-v0.1.tabulartext-classificationn<1K0 likes23 downloads7mo agoHugging Face06Vietnamese-Camel /thematic_generalizationtextn<1K0 likes1 downloads1y agoHugging Face

Listings come live from the Hugging Face Hub API. CoolFace does not host these files.