The [VisionEncoderDecoderModel] can be used to initialize an image-to-text-sequence model with any
pretrained vision autoencoding model as the encoder (e.g. ViT, BEiT, DeiT)
and any pretrained language model as the decoder (e.g. RoBERTa, GPT2, BERT).
The effectiveness of initializing image-to-text-sequence models with pretrained checkpoints has been shown in (for
example) TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models by Minghao Li, Tengchao Lv, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang,
Zhoujun Li, Furu Wei.
An example of how to use a [VisionEncoderDecoderModel] for inference can be seen in TrOCR.
VisionEncoderDecoderConfig
[[autodoc]] VisionEncoderDecoderConfig
VisionEncoderDecoderModel
[[autodoc]] VisionEncoderDecoderModel
    - forward
    - from_encoder_decoder_pretrained
