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iconitech
/
nfl-scouting-expert-v1

Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:41
loss:TripletLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use iconitech/nfl-scouting-expert-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use iconitech/nfl-scouting-expert-v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("iconitech/nfl-scouting-expert-v1")
    
    sentences = [
        "elite ball production DB",
        "rarely gets his head around and allows catches in phase",
        "times his breaks and plucks interceptions away from receivers",
        "sprays throws and forces receivers to adjust behind them"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
nfl-scouting-expert-v1
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
iconitech's picture
iconitech
update model improvements
88bf055 verified about 1 year ago
  • 1_Pooling
    add model files about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    12.4 kB
    update model improvements about 1 year ago
  • config.json
    551 Bytes
    Add model files about 1 year ago
  • config_sentence_transformers.json
    199 Bytes
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  • model.safetensors
    438 MB
    xet
    update model improvements about 1 year ago
  • modules.json
    349 Bytes
    Add model files about 1 year ago
  • sentence_bert_config.json
    53 Bytes
    Add model files about 1 year ago
  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    1.62 kB
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  • vocab.txt
    232 kB
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