How to use onelevelstudio/M-MPNET-BASE with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("onelevelstudio/M-MPNET-BASE") 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 onelevelstudio/M-MPNET-BASE with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("onelevelstudio/M-MPNET-BASE") model = AutoModel.from_pretrained("onelevelstudio/M-MPNET-BASE", device_map="auto")
https://huggingface.co/onelevelstudio/M-MPNET-BASE/resolve/d44012e5c865d5db8a1a04eb2b47d10165780ab8/tokenizer.json
hf download hf://onelevelstudio/M-MPNET-BASE@d44012e5c865d5db8a1a04eb2b47d10165780ab8/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/onelevelstudio/M-MPNET-BASE/resolve/d44012e5c865d5db8a1a04eb2b47d10165780ab8/tokenizer.json
