crumb/

Wizard-EvolInstruct70k-k32

centers.pt in the files is a 32x384 matrix including the centers of each cluster. I use sentence-transformers/all-MiniLM-L6-v2 to encode text. import torch from sentence_transformers import SentenceTransformer

sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2') embeddings = torch.tensor(model.encode(sentences)) centers = torch.load("centers.pt")… See the full description on the dataset page: https://huggingface.co/datasets/crumb/Wizard-EvolInstruct70k-k32.