How to use avsolatorio/00-600-11-1-6-2-0-0-768-512-cm_NOI_BAAI_bge-base-en-v1.5-20240704035539-latest with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("avsolatorio/00-600-11-1-6-2-0-0-768-512-cm_NOI_BAAI_bge-base-en-v1.5-20240704035539-latest") 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 avsolatorio/00-600-11-1-6-2-0-0-768-512-cm_NOI_BAAI_bge-base-en-v1.5-20240704035539-latest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="avsolatorio/00-600-11-1-6-2-0-0-768-512-cm_NOI_BAAI_bge-base-en-v1.5-20240704035539-latest")
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("avsolatorio/00-600-11-1-6-2-0-0-768-512-cm_NOI_BAAI_bge-base-en-v1.5-20240704035539-latest") model = AutoModel.from_pretrained("avsolatorio/00-600-11-1-6-2-0-0-768-512-cm_NOI_BAAI_bge-base-en-v1.5-20240704035539-latest")
