How to use avsolatorio/01-100-11-1-2-2-0-0-cls-normed-384-512_GIST_BAAI_bge-small-en-v1.5-20240208121054-best with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("avsolatorio/01-100-11-1-2-2-0-0-cls-normed-384-512_GIST_BAAI_bge-small-en-v1.5-20240208121054-best") 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/01-100-11-1-2-2-0-0-cls-normed-384-512_GIST_BAAI_bge-small-en-v1.5-20240208121054-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="avsolatorio/01-100-11-1-2-2-0-0-cls-normed-384-512_GIST_BAAI_bge-small-en-v1.5-20240208121054-best")
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("avsolatorio/01-100-11-1-2-2-0-0-cls-normed-384-512_GIST_BAAI_bge-small-en-v1.5-20240208121054-best") model = AutoModel.from_pretrained("avsolatorio/01-100-11-1-2-2-0-0-cls-normed-384-512_GIST_BAAI_bge-small-en-v1.5-20240208121054-best")
