Instructions to use gabrielloiseau/ModernBERT-base-authorship-verification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gabrielloiseau/ModernBERT-base-authorship-verification with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gabrielloiseau/ModernBERT-base-authorship-verification") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
SentenceTransformer based on answerdotai/ModernBERT-base
This is a sentence-transformers model finetuned from answerdotai/ModernBERT-base. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
Model Details
Model Description
- Model Type: Sentence Transformer
- Base model: answerdotai/ModernBERT-base
- Maximum Sequence Length: 8192 tokens
- Output Dimensionality: 768 dimensions
- Similarity Function: Cosine Similarity
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Model tree for gabrielloiseau/ModernBERT-base-authorship-verification
Base model
answerdotai/ModernBERT-base