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antarge
/
minilm-finetuned

Sentence Similarity
Transformers
PyTorch
sentence-transformers
English
bert
feature-extraction
finetuned
all-MiniLM
Model card Files Files and versions
xet
Community

Instructions to use antarge/minilm-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use antarge/minilm-finetuned with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("antarge/minilm-finetuned")
    model = AutoModel.from_pretrained("antarge/minilm-finetuned", device_map="auto")
  • sentence-transformers

    How to use antarge/minilm-finetuned with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("antarge/minilm-finetuned")
    
    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]
  • Notebooks
  • Google Colab
  • Kaggle
minilm-finetuned
177 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
antarge's picture
antarge
Upload example.py with huggingface_hub
a731a91 verified 22 days ago
  • .gitattributes
    1.52 kB
    initial commit 22 days ago
  • README.md
    818 Bytes
    Upload README.md with huggingface_hub 22 days ago
  • config.json
    179 Bytes
    Upload config.json with huggingface_hub 22 days ago
  • example.py
    232 Bytes
    Upload example.py with huggingface_hub 22 days ago
  • model.pt
    88.4 MB
    xet
    Upload model.pt with huggingface_hub 22 days ago
  • pytorch_model.bin
    88.4 MB
    xet
    Upload pytorch_model.bin with huggingface_hub 22 days ago