Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use intellya22/new-test-model-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intellya22/new-test-model-ar with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intellya22/new-test-model-ar") 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] - Transformers
How to use intellya22/new-test-model-ar with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("intellya22/new-test-model-ar") model = AutoModel.from_pretrained("intellya22/new-test-model-ar") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 1 year ago
by
SFconvertbot