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dice-group / dice-embeddings

Hardware-agnostic Framework for Large-scale Knowledge Graph Embeddings
MIT License
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Continual Training and Downloading Pretrained models #239

Closed Demirrr closed 6 months ago

Demirrr commented 6 months ago

CL

## Train
dicee --continual_learning KeciFamilyRun --path_single_kg "KGs/Family/family-benchmark_rich_background.owl" --model Keci --path_to_store_single_run KeciFamilyRun --backend rdflib --eval_model None
## Resume Training
dicee --continual_learning KeciFamilyRun --path_single_kg "KGs/Family/family-benchmark_rich_background.owl" --model Keci --path_to_store_single_run KeciFamilyRun --backend rdflib --eval_model None

Download and Use

from dicee import KGE
mure = KGE(url="https://files.dice-research.org/projects/DiceEmbeddings/YAGO3-10-Pykeen_MuRE-dim128-epoch256-KvsAll")
quate = KGE(url="https://files.dice-research.org/projects/DiceEmbeddings/YAGO3-10-Pykeen_QuatE-dim128-epoch256-KvsAll")
keci = KGE(url="https://files.dice-research.org/projects/DiceEmbeddings/YAGO3-10-Keci-dim128-epoch256-KvsAll")
quate.predict_topk(h=["Mongolia"],r=["isLocatedIn"],topk=3)
# [('Asia', 0.9894362688064575), ('Europe', 0.01575559377670288), ('Tadanari_Lee', 0.012544365599751472)]
keci.predict_topk(h=["Mongolia"],r=["isLocatedIn"],topk=3)
# [('Asia', 0.6522021293640137), ('Chinggis_Khaan_International_Airport', 0.36563414335250854), ('Democratic_Party_(Mongolia)', 0.19600993394851685)]
mure.predict_topk(h=["Mongolia"],r=["isLocatedIn"],topk=3)
# [('Asia', 0.9996906518936157), ('Ulan_Bator', 0.0009907372295856476), ('Philippines', 0.0003116439620498568)]