RAG Model without DPR
Hello everyone,
I am interesting in studying how RAG generator answers questions without the DPR retriever but with other passages / contexts identified by other methods.

For example in the code below

```from transformers import RagRetriever
from transformers import RagTokenizer, RagRetriever, RagTokenForGeneration

retriever = RagRetriever.from_pretrained(’./rag-token-nq’, indexed_dataset=dataset)
tokenizer = RagTokenizer.from_pretrained("./rag-token-nq")
model = RagTokenForGeneration.from_pretrained("./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_ids = input_dict[“input_ids”]

model = RagTokenForGeneration.from_pretrained(“facebook/rag-token-nq”, retriever=retriever)

generated_ids = model.generate(input_ids=input_ids, labels=input_dict[“labels”])

generated_string = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
print(generated_string) 
```

In the line 
```input_dict = tokenizer.prepare_seq2seq_batch(“How many people live in Paris?”, “In Paris, there are 10 million people.”, return_tensors=“pt”) ```
, I want to use “How many people live in Paris ?” as the question and “In Paris, there are 10 million people.” the passage/context which should be used to generate the answer.

Kindly let me know how to do this?

Is my understanding of the code correct and if not, how to go about it?

Thanks,
Krishanu
Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.
Could you ask your question on the [forum](https://discusss.huggingface.co) instead? Feel free to tag @patrickvonplaten or @lhoestq on the forum, they'll probably be able to answer your quesitons :).

Thanks!