How to fine tune T5 like for translation tasks?
# ❓ Questions & Help


## Details
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I want to pass 100000's of training instances to this syntax, but it says its limit is only 512. I am passing list of strings.
input_ids = tokenizer.encode('translate English to German: The house is wonderful. </s>', return_tensors='pt')
lm_labels = tokenizer.encode('Das Haus ist wunderbar. </s>', return_tensors='pt')
model(input_ids=input_ids, lm_labels=lm_labels)

And for 512 instances, it is not training, it is finishing in seconds without loading weights and training.

Could you explain how to fine-tune it in the correct way and use the fine-tuned model for the generation?
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**A link to original question on Stack Overflow**: 
see https://github.com/huggingface/transformers/issues/3576