I trained a BERT based encoder decoder model: ed_model I tokenized the input with: txt = "I love huggingface" inputs = input_tokenizer(txt, return_tensors="pt").to(device) print(inputs) The output clearly shows that a input_ids is the return dict {'input_ids': tensor([[ 101, 5660, 7975, 2127, 2…

I get a "You have to specify either input_ids or inputs_embeds" error, but I do specify the input ids

TopRightExit September 28, 2021, 11:24pm 4

Hi @ugoren , how did you solve this issue? I encountered the same issue trying to train the EncoderDecodeModel using the seq2seqtrainer.

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