How to use machinev/model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("machinev/model") sentences = [ "the main power cable is connected with LPT ", "the main power cable is connected with LPT ", "the main power cable is connected with LPT ", "/content/sample_data/images/LPT (2).jpeg" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/machinev/model/resolve/main/vocab.json
hf download hf://machinev/model/vocab.json
curl -L -o vocab.json https://huggingface.co/machinev/model/resolve/main/vocab.json
