| import streamlit as st | |
| from transformers import RagTokenizer, RagRetriever, RagTokenForGeneration | |
| tokenizer = RagTokenizer.from_pretrained("facebook/rag-token-nq") | |
| retriever = RagRetriever.from_pretrained("facebook/rag-token-nq", index_name="exact", use_dummy_dataset=True) | |
| model = RagTokenForGeneration.from_pretrained("facebook/rag-token-nq", retriever=retriever) | |
| input_dict = tokenizer.prepare_seq2seq_batch("who holds the record in 100m freestyle", return_tensors="pt") | |
| generated = model.generate(input_ids=input_dict["input_ids"]) | |
| outstring = tokenizer.batch_decode(generated, skip_special_tokens=True)[0] | |
| print(outstring) | |
| st.write(outstring) | |