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microsoft
/
harrier-oss-v1-270m

Feature Extraction
sentence-transformers
Safetensors
Transformers
gemma3_text
mteb
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use microsoft/harrier-oss-v1-270m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use microsoft/harrier-oss-v1-270m with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("microsoft/harrier-oss-v1-270m")
    
    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 microsoft/harrier-oss-v1-270m with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="microsoft/harrier-oss-v1-270m")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("microsoft/harrier-oss-v1-270m")
    model = AutoModel.from_pretrained("microsoft/harrier-oss-v1-270m")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
harrier-oss-v1-270m
571 MB
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  • 1 contributor
History: 2 commits
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
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  • modules.json
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  • mteb_v2_eval_prompts.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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