Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

universalml
/
Nepali_Embedding_Model

Sentence Similarity
sentence-transformers
Safetensors
English
Nepali
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:45199
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use universalml/Nepali_Embedding_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use universalml/Nepali_Embedding_Model with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("universalml/Nepali_Embedding_Model")
    
    sentences = [
        "मैले विचार गर्नुपर्ने कलेजहरू के के हुन्, विचार गर्नुपर्ने कारकहरू: केएमसी म्यानिपल वा केएमसी मंगोलमा?",
        "मंगलोर शान्त वा हिंस्रक स्थान हो?",
        "पुरुषहरूको तुलनामा महिलाहरूको लागि यौनिक आनन्द बढी हुन्छ कि हुँदैन?",
        "के कसैले केएमसी मानिपाल र मंगलोरको संक्षिप्त तुलना गर्न सक्छ?"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
Nepali_Embedding_Model
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
universalml's picture
universalml
Update README.md
b7a62f3 verified over 1 year ago
  • 1_Pooling
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • .gitattributes
    1.57 kB
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • README.md
    4.18 kB
    Update README.md over 1 year ago
  • config.json
    725 Bytes
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • config_sentence_transformers.json
    201 Bytes
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • model.safetensors
    2.24 GB
    xet
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • modules.json
    349 Bytes
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • sentence_bert_config.json
    53 Bytes
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • special_tokens_map.json
    964 Bytes
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • tokenizer.json
    17.1 MB
    xet
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago
  • tokenizer_config.json
    1.18 kB
    Duplicate from universalml0/finetuned_embedding_model_e5-large-multilingual-large over 1 year ago