How to use longsteel/embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("longsteel/embedding", 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]
How to use longsteel/embedding with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("longsteel/embedding", trust_remote_code=True, device_map="auto")
