From 5ff0d6d7d091921bda00a84448d14c87c0c10379 Mon Sep 17 00:00:00 2001 From: Patrick von Platen Date: Fri, 25 Sep 2020 16:58:29 +0200 Subject: [PATCH] Update README.md --- model_cards/facebook/rag-token-nq/README.md | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/model_cards/facebook/rag-token-nq/README.md b/model_cards/facebook/rag-token-nq/README.md index 0db24fb14..f427ab020 100644 --- a/model_cards/facebook/rag-token-nq/README.md +++ b/model_cards/facebook/rag-token-nq/README.md @@ -14,12 +14,9 @@ retriever = RagRetriever.from_pretrained("facebook/rag-token-nq", index_name="ex model = RagTokenForGeneration.from_pretrained("facebook/rag-token-nq", retriever=retriever) input_dict = tokenizer.prepare_seq2seq_batch("How many people live in Paris?", "In Paris, there are 10 million people.", return_tensors="pt") -outputs = model(input_ids=input_dict["input_ids"], labels=input_dict["labels"]) - -# outputs.loss should give 76.1230 generated = model.generate(input_ids=input_dict["input_ids"]) -generated_string = tokenizer.batch_decode(generated, skip_special_tokens=True) +print(tokenizer.batch_decode(generated, skip_special_tokens=True)[0]) -# generated_string should give 270,000 -> not quite correct the answer, but it also only uses a dummy index +# generated_string should give 270,000,000 -> a bit too many I think ```