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Unverified Commit 5ff0d6d7 authored by Patrick von Platen's avatar Patrick von Platen Committed by GitHub
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Update README.md

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model_cards/facebook/rag-token-nq/README.md
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...@@ -14,12 +14,9 @@ retriever = RagRetriever.from_pretrained("facebook/rag-token-nq", index_name="ex ...@@ -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) 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") 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 = 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
``` ```
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