| import gradio as gr | |
| import torch | |
| from transformers import AutoTokenizer, AutoModel | |
| def get_embeddings(text): | |
| tokenizer = AutoTokenizer.from_pretrained("GroNLP/bert-base-dutch-cased") | |
| model = AutoModel.from_pretrained("GroNLP/bert-base-dutch-cased", output_hidden_states=True) | |
| sent = str(text) | |
| encoded = tokenizer.encode_plus(sent, return_tensors="pt") | |
| with torch.no_grad(): | |
| output = model(**encoded) | |
| states = output.hidden_states | |
| return states | |
| iface = gr.Interface(fn=get_embeddings,inputs="text",outputs="text") | |
| iface.launch() |