Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers.js
English
modernbert
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use nomic-ai/modernbert-embed-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nomic-ai/modernbert-embed-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nomic-ai/modernbert-embed-base") 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] - Transformers.js
How to use nomic-ai/modernbert-embed-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'nomic-ai/modernbert-embed-base'); - Notebooks
- Google Colab
- Kaggle
Update `base_model_relation` to `finetune` (#11)
Browse files- Update `base_model_relation` to `finetune` (4ed9ae79014d2d47321e2a4a1a5f9a1f6089942b)
README.md
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# ModernBERT Embed
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base_model_relation: finetune
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# ModernBERT Embed
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