datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
BATIS
license: cc-by-nc-4.0
BATIS: Bayesian Approaches for Targeted Improvement of Species Distribution Models
This repository contains the dataset used in experiments shown in BATIS: Bayesian Approaches for Targeted Improvement of Species Distribution Models. To download the dataset, you can use the load_dataset function from HuggingFace. For example :
from datasets import load_dataset
# Training Split for Kenya
training_kenya = load_dataset("cathv/BATIS", name="Kenya"… See the full description on the dataset page: https://huggingface.co/datasets/cathv/BATIS.bdnb_2023-11.a_batiment_construction_FFO_METROPOLE_4326batik-processedbdnb_2023-11.a_rel_batiment_groupe_bdtopo_zoa_39bdnb_2023-11.a_batiment_construction_FFO_MET_4326_outer_join_h3bdnb_2023-11.a_batiment_groupe_argiles_29dataset-batik-trl-sft
Dataset Batik TRL-SFT
Dataset percakapan berformat SFT (Supervised Fine-Tuning) untuk melatih model bahasa sebagai asisten pakar budaya Batik Nusantara. Digunakan untuk fine-tuning model Wastra.ai (berbasis Qwen2.5-1.5B-Instruct) pada proyek BatikLens.
Dataset Description
Dataset ini berisi lebih dari 3 juta contoh percakapan seputar batik Indonesia, mencakup topik:
Sejarah dan asal-usul batik di berbagai daerah
Filosofi dan makna motif batik (Parang, Kawung… See the full description on the dataset page: https://huggingface.co/datasets/maftuh-main/dataset-batik-trl-sft.ferroelectricity_and_metallicity_in_BaTiO3_JMCC2021
Cite this dataset Michel, V. F., Esswein, T., and Spaldin, N. A. ferroelectricity and metallicity in BaTiO3 JMCC2021. ColabFit, 2024. https://doi.org/10.60732/9abdf618
This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_1t2xs8bzygtp_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/ferroelectricity_and_metallicity_in_BaTiO3_JMCC2021.bdnb_2023-11.a_batiment_groupe_adresse_01bdnb_2023-11.a_rel_batiment_groupe_bdtopo_bat_01bdnb_2023-11.a_batiment_groupe_rnc_12bdnb_2023-11.a_batiment_groupe_geospx_69bdnb_2023-11.a_rel_batiment_groupe_qpv_79bdnb_2023-11.a_rel_batiment_groupe_bpe_59bdnb_2023-11.a_batiment_groupe_rnc_59bdnb_2023-11.a_batiment_groupe_dle_elec_multimillesime_39bdnb_2023-11.a_rel_batiment_groupe_parcelle_01bdnb_2023-11.a_batiment_groupe_merimee_66bdnb_2023-11.a_rel_batiment_groupe_merimee_59BATIS
license: cc-by-nc-4.0
BATIS: Bayesian Approaches for Targeted Improvement of Species Distribution Models
This repository contains the dataset used in experiments shown in BATIS: Bayesian Approaches for Targeted Improvement of Species Distribution Models. To download the dataset, you can use the load_dataset function from HuggingFace. For example :
from datasets import load_dataset
# Training Split for Kenya
training_kenya = load_dataset("anonsubmit/BATIS", name="Kenya"… See the full description on the dataset page: https://huggingface.co/datasets/anonsubmit/BATIS.bdnb_2023-11.a_rel_batiment_groupe_dpe_logement_01bdnb_2023-11.a_rel_batiment_construction_rnb_01bdnb_2023-11.a_batiment_groupe_bdtopo_bat_METROPOLEbdnb_2023-11.a_batiment_construction_METROPOLEbdnb_2023-11.a_batiment_groupe_geospx_89bdnb_2023-11.a_rel_batiment_groupe_bpe_09bdnb_2023-11.a_batiment_construction_19bdnb_2023-11.a_batiment_groupe_bdtopo_bat_09bdnb_2023-11.a_rel_batiment_groupe_proprietaire_METROPOLEbdnb_2023-11.a_batiment_groupe_adresse_19