How to use Corran/CCRO2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Corran/CCRO2")
How to use Corran/CCRO2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Corran/CCRO2", 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]
c5c4986
1
2
3
4
5
6
7
8
9
10
11
12
13
14
[ { "idx": 0, "name": "0", "path": "", "type": "sentence_transformers.models.Transformer" }, { "idx": 1, "name": "1", "path": "1_Pooling", "type": "sentence_transformers.models.Pooling" } ]