| from transformers import AutoTokenizer | |
| from optimum.onnxruntime import ORTModelForFeatureExtraction | |
| import torch | |
| tokenizer = AutoTokenizer.from_pretrained("./models/optimum/all-MiniLM-L6-v2") | |
| model = ORTModelForFeatureExtraction.from_pretrained("./models/optimum/all-MiniLM-L6-v2") | |
| inputs = tokenizer("My name is Philipp and I live in Germany.", return_tensors="np") | |
| outputs = model(**inputs) | |
| last_hidden_state = outputs.last_hidden_state | |
| # no mean pooling | |
| print(list(last_hidden_state.shape)) | |