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nickprock/sentence-bert-base-italian-uncased
Sentence Similarity • 0.1B • Updated • 44k • • 10 -
nickprock/sentence-bert-base-italian-xxl-uncased
Sentence Similarity • 0.1B • Updated • 18.9k • • 16 -
nickprock/multi-sentence-BERTino
Sentence Similarity • 67.6M • Updated • 1.62k • • 8 -
nickprock/splade-bert-base-italian-xxl-uncased-cv
Feature Extraction • 0.1B • Updated • 184 • 9
Nicola Procopio
nickprock
AI & ML interests
Digital Health
Semantic Search - Vector Search
Organizations
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Is Cosine-Similarity of Embeddings Really About Similarity?
Paper • 2403.05440 • Published • 3 -
GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning
Paper • 2402.16829 • Published • 1 -
Make Your LLM Fully Utilize the Context
Paper • 2404.16811 • Published • 55 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 116
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nickprock/bert-italian-finetuned-ner
Token Classification • 0.1B • Updated • 159 • 8 -
nickprock/modernbert-italian-finetuned-ner
Token Classification • 0.1B • Updated • 12 • 1 -
nickprock/bert-finetuned-ner-ontonotes
Token Classification • 0.1B • Updated • 10 -
nickprock/distilbert-finetuned-ner-ontonotes
Token Classification • 65.2M • Updated • 18
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nickprock/sentence-bert-base-italian-uncased
Sentence Similarity • 0.1B • Updated • 44k • • 10 -
nickprock/sentence-bert-base-italian-xxl-uncased
Sentence Similarity • 0.1B • Updated • 18.9k • • 16 -
nickprock/multi-sentence-BERTino
Sentence Similarity • 67.6M • Updated • 1.62k • • 8 -
nickprock/splade-bert-base-italian-xxl-uncased-cv
Feature Extraction • 0.1B • Updated • 184 • 9
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nickprock/bert-italian-finetuned-ner
Token Classification • 0.1B • Updated • 159 • 8 -
nickprock/modernbert-italian-finetuned-ner
Token Classification • 0.1B • Updated • 12 • 1 -
nickprock/bert-finetuned-ner-ontonotes
Token Classification • 0.1B • Updated • 10 -
nickprock/distilbert-finetuned-ner-ontonotes
Token Classification • 65.2M • Updated • 18
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Is Cosine-Similarity of Embeddings Really About Similarity?
Paper • 2403.05440 • Published • 3 -
GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning
Paper • 2402.16829 • Published • 1 -
Make Your LLM Fully Utilize the Context
Paper • 2404.16811 • Published • 55 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 116