Nomic Embed v2
Collection
Multilingual Embedding Models • 5 items • Updated • 24
How to use nomic-ai/nomic-embed-text-v2-moe-unsupervised with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("nomic-ai/nomic-embed-text-v2-moe-unsupervised", trust_remote_code=True)
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]nomic-embed-text-v2-moe-unsupervised is multilingual MoE Text Embedding model. This is a checkpoint after contrastive pretraining from multi-stage contrastive training of the
final model.
If you want to use a model to extract embeddings, we suggest using nomic-embed-text-v2-moe