How to use juampahc/bge-m3-m2v-1024 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("juampahc/bge-m3-m2v-1024") 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]
How to use juampahc/bge-m3-m2v-1024 with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("juampahc/bge-m3-m2v-1024") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape)
https://huggingface.co/juampahc/bge-m3-m2v-1024/resolve/main/modules.json
hf download hf://juampahc/bge-m3-m2v-1024/modules.json
curl -L -o modules.json https://huggingface.co/juampahc/bge-m3-m2v-1024/resolve/main/modules.json
