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GSR-608001
/
avvaiyar-embedding-model

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:725
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use GSR-608001/avvaiyar-embedding-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use GSR-608001/avvaiyar-embedding-model with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("GSR-608001/avvaiyar-embedding-model")
    
    sentences = [
        "What happens if someone completely ignores the wisdom of 'இணக்கம் அறிந்து இணங்கு'?",
        "\nAathichoodi Ethical Wisdom\n\nVerse: இலவம் பஞ்சில் துயில்\n\nExplanation:\nOptimal cognitive performance and long-term physiological health are predicated on high-quality restorative sleep and the ergonomics of rest. By specifying the use of natural, soft materials like silk cotton, this principle emphasizes the importance of environmental quality in the recovery process. In a high-pressure modern society, prioritizing rest is not a luxury but a strategic necessity, as the quality of one's sleep directly correlates with emotional regulation, decision-making clarity, and the biological maintenance required for a productive life.\n",
        "\nAathichoodi Ethical Wisdom\n\nVerse: வாது முற்கூறேல்\n\nExplanation:\nResist the urge to initiate aggressive debates or participate in the dissemination of unverified claims and divisive rhetoric. Engaging in preemptive argumentation or speculative discourse destabilizes social harmony and reflects a lack of intellectual maturity. Instead, adopt a stance of reflective listening and evidence-based reasoning, ensuring that your contributions to a conversation are constructive rather than combative. By refusing to be the progenitor of conflict or gossip, you preserve your credibility and contribute to a culture of thoughtful, high-fidelity exchange.\n",
        "\nAathichoodi Ethical Wisdom\n\nVerse: இணக்கம் அறிந்து இணங்கு\n\nExplanation:\nThe quality of an individual’s character and their trajectory of growth are significantly influenced by their social ecosystem; therefore, selective association is a critical component of strategic personal development. This principle necessitates a deep psychological vetting process before committing to any professional or personal partnership. One must analyze the underlying values, ethical track records, and behavioral patterns of potential associates to ensure alignment with one's own integrity. In the context of modern networking and collaborative systems, it suggests that shared purpose is only sustainable when built on a foundation of mutual virtue and proven character.\n"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
avvaiyar-embedding-model
488 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
GSR-608001's picture
GSR-608001
Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050)
2d0184e verified 5 months ago
  • 1_Pooling
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • .gitattributes
    1.57 kB
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • README.md
    28.1 kB
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • config.json
    785 Bytes
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • config_sentence_transformers.json
    295 Bytes
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • model.safetensors
    471 MB
    xet
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • modules.json
    368 Bytes
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • sentence_bert_config.json
    60 Bytes
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • tokenizer.json
    17.1 MB
    xet
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago
  • tokenizer_config.json
    561 Bytes
    Fine-tuned on 725 Aathichoodi pairs (4 epochs, multilingual-e5-small, RTX 3050) 5 months ago