Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:19545
loss:DenoisingAutoEncoderLoss
text-embeddings-inference
Instructions to use shethjenil/demo_finetuned_Embedding_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use shethjenil/demo_finetuned_Embedding_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shethjenil/demo_finetuned_Embedding_model") 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
Ctrl+K