Sentence Similarity
sentence-transformers
PyTorch
Transformers
Divehi
bert
feature-extraction
text-embeddings-inference
Instructions to use ashraq/tsdae-bert-base-dv-news-title with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ashraq/tsdae-bert-base-dv-news-title with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ashraq/tsdae-bert-base-dv-news-title") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use ashraq/tsdae-bert-base-dv-news-title with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ashraq/tsdae-bert-base-dv-news-title") model = AutoModel.from_pretrained("ashraq/tsdae-bert-base-dv-news-title") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot