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model_cards/facebook/rag-token-base/README.md

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+## RAG
+
+This is a "base" version of the RAG-Token Model of the the paper [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://arxiv.org/pdf/2005.11401.pdf) 
+by Patrick Lewis, Ethan Perez, Aleksandara Piktus et al.
+
+## Usage:
+
+```python
+from transformers import RagTokenizer, RagRetriever, RagSequenceForGeneration
+
+tokenizer = RagTokenizer.from_pretrained("facebook/rag-token-base")
+retriever = RagRetriever.from_pretrained("facebook/rag-token-base", index_name="exact", use_dummy_dataset=True)
+model = RagSequenceForGeneration.from_pretrained("facebook/rag-token-base", retriever=retriever)
+
+input_ids = tokenizer("What is the largest country in the world?", return_tensors="pt").input_ids
+
+generated = model.generate(input_ids=input_ids)
+generated_string = tokenizer.batch_decode(generated, skip_special_tokens=True)
+
+# => should give [' russia']. Pretty good answer for just having just a dummy dataset.
+```