Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

Alibaba-NLP
/
gte-modernbert-base

Sentence Similarity
Transformers
PyTorch
ONNX
Safetensors
sentence-transformers
Transformers.js
English
modernbert
feature-extraction
mteb
embedding
text-embeddings-inference
Model card Files Files and versions
xet
Community
17

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")
  • 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
gte-modernbert-base / onnx
1.93 GB
Ctrl+K
Ctrl+K
  • 7 contributors
History: 1 commit
thenlper's picture
thenlper
Upload ONNX weights (#5)
586ae96 verified over 1 year ago
  • model.onnx
    596 MB
    xet
    Upload ONNX weights (#5) over 1 year ago
  • model_bnb4.onnx
    217 MB
    xet
    Upload ONNX weights (#5) over 1 year ago
  • model_fp16.onnx
    298 MB
    xet
    Upload ONNX weights (#5) over 1 year ago
  • model_int8.onnx
    150 MB
    xet
    Upload ONNX weights (#5) over 1 year ago
  • model_q4.onnx
    224 MB
    xet
    Upload ONNX weights (#5) over 1 year ago
  • model_q4f16.onnx
    140 MB
    xet
    Upload ONNX weights (#5) over 1 year ago
  • model_quantized.onnx
    150 MB
    xet
    Upload ONNX weights (#5) over 1 year ago
  • model_uint8.onnx
    150 MB
    xet
    Upload ONNX weights (#5) over 1 year ago