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openpecha
/
Finetuned_Alibaba_Large

Sentence Similarity
sentence-transformers
Safetensors
new
feature-extraction
Generated from Trainer
dataset_size:7075
loss:MultipleNegativesRankingLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use openpecha/Finetuned_Alibaba_Large with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("openpecha/Finetuned_Alibaba_Large", trust_remote_code=True)
    
    sentences = [
        "What is the name of the monastery founded by Karma Rolpai Dorje?",
        "Amid the splendor of this natural beauty stood the monastery called Karma Shar Tsong Ridro, which is a famous place in the religious history of Tibet. It was founded by Karma Rolpai Dorje, the fourth reincarnation of Karmapa, who himself was the first incarnation recognized in Tibet; and it was at this monastery that our great reformer Tsongkhapa was initiated as a monk in the fourteenth century of the Christian era.",
        "In the Year of the Water Bird (1933), Thupten Gyatso, the Thirteenth Dalai Lama, departed from this world. This event left the people of Tibet desolate, as he had done much for the peace and welfare of Tibet. Following his death, the people decided to build a golden mausoleum of special magnificence as a token of their homage and respect, which was erected inside the Potala Palace in Lhasa.",
        "Mr. Nehru's personality had impressed me very much. Although the mantle of Mahatma Gandhi had fallen on him, I could not catch any glimpse of spiritual fervor in him; but I saw him as a brilliant practical statesman, with a masterly grasp of international politics, and he showed me that he had a profound love for his country and faith in his people. For their welfare and progress, he was firm in the pursuit of peace."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
Finetuned_Alibaba_Large / 1_Pooling
594 Bytes
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
tenzin3's picture
tenzin3
embedding model smaller files
17f9526 about 2 years ago
  • .ipynb_checkpoints
    embedding model smaller files about 2 years ago
  • config.json
    297 Bytes
    embedding model smaller files about 2 years ago