Sentence Similarity
Transformers
PyTorch
ONNX
Safetensors
sentence-transformers
Transformers.js
English
modernbert
feature-extraction
mteb
embedding
text-embeddings-inference
Instructions to use Alibaba-NLP/gte-modernbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alibaba-NLP/gte-modernbert-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Alibaba-NLP/gte-modernbert-base") model = AutoModel.from_pretrained("Alibaba-NLP/gte-modernbert-base", device_map="auto") - sentence-transformers
How to use Alibaba-NLP/gte-modernbert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Alibaba-NLP/gte-modernbert-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 Alibaba-NLP/gte-modernbert-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'Alibaba-NLP/gte-modernbert-base'); - Inference
- Notebooks
- Google Colab
- Kaggle
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## Citation
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If you find our paper or models helpful, feel free to give us a cite.
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## Hiring
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We have open positions for **Research Interns** and **Full-Time Researchers** to join our team at Tongyi Lab.
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We are seeking passionate individuals with expertise in representation learning, LLM-driven information retrieval, Retrieval-Augmented Generation (RAG), and agent-based systems.
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Our team is located in the vibrant cities of **Beijing** and **Hangzhou**.
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If you are driven by curiosity and eager to make a meaningful impact through your work, we would love to hear from you. Please submit your resume along with a brief introduction to <a href="mailto:dingkun.ldk@alibaba-inc.com">dingkun.ldk@alibaba-inc.com</a>.
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## Citation
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If you find our paper or models helpful, feel free to give us a cite.
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