How to use llm-semantic-router/multi-modal-embed-small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("llm-semantic-router/multi-modal-embed-small", dtype="auto")
How to use llm-semantic-router/multi-modal-embed-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("llm-semantic-router/multi-modal-embed-small") 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]
