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evalllm2026-reranker-geonames-finetuned – AI Model by rarmingaud | AlphaNeural AI
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evalllm2026-reranker-geonames-finetuned
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sentence-transformers
safetensors
xlm-roberta
evalllm2026
cross-encoder
reranker
LambdaLoss
text-ranking
fr
en
BAAI/bge-m3
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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cea-list-ia/evalllm2026-reranker-geonames-finetuned
This model was trained by the CEA-LIST to participate in the
evalLLM2026 challenge
.
Model Description
Trained by:
CEA-LIST
Task:
Entity Linking (GeoNames)
Type:
Reranker (Cross-Encoder)
Training Data:
Wikipedia, further trained on the training data of the challenge.
This reranker is a cross-encoder designed to improve the candidates selected by an embedding model.
Usage
Query Prefix
To use this model, you should prompt it with the following query prefix:
Represent this geographical sentence for retrieving relevant GeoNames terms:
More Information
For more details, please refer to the
GitHub repository
.
