BART-base save_pretrained triggers a warning about GenerationConfig

[Kripner]

System Info

• transformers version: 4.37.0
• Platform: Linux-6.5.0-15-generic-x86_64-with-glibc2.31
• Python version: 3.10.13
• Huggingface_hub version: 0.20.3
• Safetensors version: 0.4.1
• Accelerate version: 0.26.1
• Accelerate config: not found
• PyTorch version (GPU?): 2.1.2 (True)
• Tensorflow version (GPU?): not installed (NA)
• Flax version (CPU?/GPU?/TPU?): not installed (NA)
• Jax version: not installed
• JaxLib version: not installed
• Using GPU in script?: Yes
• Using distributed or parallel set-up in script?: No

Who can help?

@ArthurZucker @younesbelkada

Information

• The official example scripts
• My own modified scripts

Tasks

• An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
• My own task or dataset (give details below)

Reproduction

from transformers import AutoModelForSeq2SeqLM

model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-base")
model.save_pretrained("model")

Expected behavior

Expected behavior: The model is saved without warnings.

Actual behavior: Following warning is triggered before saving the model:

Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.
Non-default generation parameters: {'early_stopping': True, 'num_beams': 4, 'no_repeat_ngram_size': 3, 'forced_bos_token_id': 0, 'forced_eos_token_id': 2}

[ArthurZucker]

Hey that is expected as it is a pretty old model! You can safely ignore this for now, otherwise they should be removed. Feel free to open an issue on the repository's discussion tab !

[github-actions]

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