Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use NetherlandsForensicInstitute/ARM64BERT-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NetherlandsForensicInstitute/ARM64BERT-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NetherlandsForensicInstitute/ARM64BERT-embedding") 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
Set document title to model name, add (non-existing) github link
Browse files
README.md
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library_name: sentence-transformers
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==========
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_Who to contact:_ fbda [at] nfi [dot] nl \
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## General
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### What is the purpose of the model
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library_name: sentence-transformers
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ARM64BERT-embedding 🦾
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======================
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_Who to contact:_ fbda [at] nfi [dot] nl \
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[GitHub repository](https://github.com/NetherlandsForensicInstitute/asmtransformers)
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## General
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### What is the purpose of the model
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