How to use ssmits/Falcon2-5.5B-multilingual-embed-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ssmits/Falcon2-5.5B-multilingual-embed-base", trust_remote_code=True) 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]
https://huggingface.co/ssmits/Falcon2-5.5B-multilingual-embed-base/resolve/main/tokenizer.json
hf download hf://ssmits/Falcon2-5.5B-multilingual-embed-base/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/ssmits/Falcon2-5.5B-multilingual-embed-base/resolve/main/tokenizer.json
