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mixedbread-ai
/
deepset-mxbai-embed-de-large-v1

Feature Extraction
sentence-transformers
ONNX
Safetensors
Transformers
Transformers.js
German
English
xlm-roberta
sentence_embedding
feature_extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community
10

Instructions to use mixedbread-ai/deepset-mxbai-embed-de-large-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use mixedbread-ai/deepset-mxbai-embed-de-large-v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("mixedbread-ai/deepset-mxbai-embed-de-large-v1")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Transformers

    How to use mixedbread-ai/deepset-mxbai-embed-de-large-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="mixedbread-ai/deepset-mxbai-embed-de-large-v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("mixedbread-ai/deepset-mxbai-embed-de-large-v1")
    model = AutoModel.from_pretrained("mixedbread-ai/deepset-mxbai-embed-de-large-v1")
  • Transformers.js

    How to use mixedbread-ai/deepset-mxbai-embed-de-large-v1 with Transformers.js:

    // npm i @huggingface/transformers
    import { pipeline } from '@huggingface/transformers';
    
    // Allocate pipeline
    const pipe = await pipeline('feature-extraction', 'mixedbread-ai/deepset-mxbai-embed-de-large-v1');
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

increased context length (at least 1k?) / multilingual gte / open source dataset?

#10 opened about 1 year ago by
aari1995

GGUF version?

#8 opened about 1 year ago by
kalle07

Continue Pretraining

#7 opened over 1 year ago by
HuggySSO

Embedding from transformers

#6 opened over 1 year ago by
tillwenke

"[...] mixture of full fine-tuning and LoRA was used to provide better generalization."

#5 opened almost 2 years ago by
bobox
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