How to use Yaldat/Yalda-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Yaldat/Yalda-Embedding") 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]
How to use Yaldat/Yalda-Embedding with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Yaldat/Yalda-Embedding") model = AutoModelForCausalLM.from_pretrained("Yaldat/Yalda-Embedding", device_map="auto")
https://huggingface.co/Yaldat/Yalda-Embedding/resolve/main/generation_config.json
hf download hf://Yaldat/Yalda-Embedding/generation_config.json
curl -L -o generation_config.json https://huggingface.co/Yaldat/Yalda-Embedding/resolve/main/generation_config.json
