Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
dataset_size:1M<n<10M
loss:MSELoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ammumadhu/Indic_Bert-8-layers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ammumadhu/Indic_Bert-8-layers with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ammumadhu/Indic_Bert-8-layers") sentences = [ "Nobody is standing", "The person staring has no vision.", "The person in black T-shirt is sitting.", "The two girls are at the amusement park." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle