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mzuama
/
E5-base-Law-indo-sample2

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:380
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use mzuama/E5-base-Law-indo-sample2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use mzuama/E5-base-Law-indo-sample2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("mzuama/E5-base-Law-indo-sample2")
    
    sentences = [
        "query: Berapa hukuman untuk kejahatan sistematis berupa penyiksaan terhadap penduduk sipil?",
        "passage: Agar bisa dikualifikasi sebagai pengaduan fitnah, harus ada pengaduan atau pemberitahuan palsu yang diajukan secara tertulis kepada pejabat yang berwenang, dan perbuatan tersebut harus mengakibatkan serangan terhadap kehormatan atau nama baik orang yang dilaporkan. (Pasal 437 ayat (1) KUHP)",
        "passage: Perbuatan mengakibatkan penderitaan fisik atau mental berat untuk memusnahkan suatu kelompok tertentu dipidana penjara paling singkat 5 tahun dan paling lama 20 tahun. (Pasal 598 KUHP)",
        "passage: Perbuatan penyiksaan yang merupakan bagian dari serangan sistematis terhadap penduduk sipil dipidana penjara paling singkat 5 tahun dan paling lama 15 tahun. (Pasal 599 huruf b KUHP)"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
E5-base-Law-indo-sample2
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
mzuama's picture
mzuama
Add new SentenceTransformer model
1311acd verified about 1 month ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
    296 Bytes
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  • model.safetensors
    1.11 GB
    xet
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  • modules.json
    368 Bytes
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  • sentence_bert_config.json
    60 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    369 Bytes
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