How to use ewin-reg/WeMM-Embedding-2B-Quantized with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ewin-reg/WeMM-Embedding-2B-Quantized", 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/ewin-reg/WeMM-Embedding-2B-Quantized/resolve/main/modules.json
hf download hf://ewin-reg/WeMM-Embedding-2B-Quantized/modules.json
curl -L -o modules.json https://huggingface.co/ewin-reg/WeMM-Embedding-2B-Quantized/resolve/main/modules.json
