Model: HydroEmbed/HydroEmbed-FITB-MiniLM-DualLoss
Author: HydroEmbed
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:2240, loss:TripletLoss, loss:CosineSimilarityLoss, arxiv:1908.10084, arxiv:1703.07737, base_model:sentence-transformers/all-MiniLM-L6-v2, base_model:finetune:sentence-transformers/all-MiniLM-L6-v2, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: sentence-transformers/all-MiniLM-L6-v2
Card metadata: tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:2240, loss:TripletLoss, loss:CosineSimilarityLoss
base_model: sentence-transformers/all-MiniLM-L6-v2
widget: source_sentence: The groundwater residence time in the Chashma-Mianwali area was estimated to be in the range of _____ years based on Tracer Lump Parameter Model (LPM) and Chlorofluorocarbons (CFCs) data.
sentences: 14–59, point scale; radar data, dissolved oxygen, source_sentence: The Grid-to-Grid hydrological model (G2G) was primarily developed to simulate river flows at a national scale but can also output simulated depth-integrated soil moisture on a _____ grid.
sentences: 89%; 11%, 1 km, catchment, source_sentence: The prime driver of flood magnitude variation in the Yellow River Basin was identified as the consecutive __________ total precipitation.
sentences: 144-day, 48, hydrologic engineering design and operation, source_sentence: Inter-basin water transfers (IBWTs) can potentially save water through changes in ________ efficiency.
sentences: spatially-constrained ordinary kriging (SC-OK), water use, 2.10–3.6 °C, source_sentence: Flood statistics often face high uncertainty in quantile estimates due to __________ observation periods.
sentences: short, convective, abstraction
pipeline_tag: sentence-similarity
library_name: sentence-transformers
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Created: 2025-05-12 19:21:06