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redis
/
langcache-embed-v3-experimental

Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
biencoder
text-classification
sentence-pair-classification
semantic-similarity
semantic-search
retrieval
reranking
Generated from Trainer
dataset_size:76349300
loss:ArcFaceInBatchLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use redis/langcache-embed-v3-experimental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use redis/langcache-embed-v3-experimental with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("redis/langcache-embed-v3-experimental")
    
    sentences = [
        "\"How much would I need to narrate a \"\"Let's Play\"\" video in order to make money from it on YouTube?\"",
        "How much money do people make from YouTube videos with 1 million views?",
        "\"How much would I need to narrate a \"\"Let's Play\"\" video in order to make money from it on YouTube?\"",
        "\"Does the sentence, \"\"I expect to be disappointed,\"\" make sense?\""
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
langcache-embed-v3-experimental
840 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
TusharGoel's picture
TusharGoel
Add exported onnx model 'model_O4.onnx'
6d900bc verified 9 months ago
  • 1_Pooling
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  • eval
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  • onnx
    Add exported onnx model 'model_O4.onnx' 9 months ago
  • .gitattributes
    1.73 kB
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  • README.md
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  • config.json
    1.21 kB
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  • config_sentence_transformers.json
    283 Bytes
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  • final_metrics.json
    296 Bytes
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  • initial_metrics.json
    426 Bytes
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  • model.safetensors
    298 MB
    xet
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  • modules.json
    229 Bytes
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  • sentence_bert_config.json
    57 Bytes
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  • special_tokens_map.json
    694 Bytes
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  • tokenizer.json
    3.58 MB
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  • tokenizer_config.json
    20.9 kB
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  • training_args.bin
    6.23 kB
    xet
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