| import torch | |
| from sentence_transformers import SentenceTransformer, util | |
| # Path to your model `.bin` file | |
| model_path = "pytorch_model.bin" | |
| # Path to your tokenizer `.json` file | |
| tokenizer_path = "tokenizer.json" | |
| # Load the model | |
| model = SentenceTransformer(model_path) | |
| # Load the tokenizer | |
| tokenizer = util.load_tokenizer(tokenizer_path) | |
| # Your sentences | |
| sentences = ["This is an example sentence", "Each sentence is converted"] | |
| # Preprocess the sentences using the tokenizer | |
| encoded_sentences = tokenizer.encode(sentences, batch_size=None, return_tensors="pt") | |
| # Get the embeddings from the model | |
| embeddings = model(encoded_sentences) | |
| # Print the embeddings | |
| print(embeddings) | |