Sentence Similarity
sentence-transformers
Safetensors
English
nomic_bert
legal
legal-retrieval
bns
indian-law
semantic-search
information-retrieval
custom_code
text-embeddings-inference
Instructions to use Ayushi054/CourtInsight-BNS-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Ayushi054/CourtInsight-BNS-Encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ayushi054/CourtInsight-BNS-Encoder", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Remove unnecessary training checkpoint files
Browse files
checkpoint-1320/sentence_bert_config.json
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"transformer_task": "feature-extraction",
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"modality_config": {
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"text": {
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"method": "forward",
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"method_output_name": "last_hidden_state"
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"module_output_name": "token_embeddings"
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}
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