mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-04 13:20:12 +06:00
8f6373c61c
* Map model_type and doc pages names * Add script * Fix typo * Quality * Manual check for Auto Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
41 lines
1.7 KiB
Plaintext
41 lines
1.7 KiB
Plaintext
<!--Copyright 2021 The HuggingFace Team. All rights reserved.
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
|
|
the License. You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
|
|
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
|
|
specific language governing permissions and limitations under the License.
|
|
-->
|
|
|
|
# Vision Encoder Decoder Models
|
|
|
|
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](vit), [BEiT](beit), [DeiT](deit))
|
|
and any pretrained language model as the decoder (*e.g.* [RoBERTa](roberta), [GPT2](gpt2), [BERT](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](https://arxiv.org/abs/2109.10282) 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](trocr).
|
|
|
|
|
|
## VisionEncoderDecoderConfig
|
|
|
|
[[autodoc]] VisionEncoderDecoderConfig
|
|
|
|
## VisionEncoderDecoderModel
|
|
|
|
[[autodoc]] VisionEncoderDecoderModel
|
|
- forward
|
|
- from_encoder_decoder_pretrained
|
|
|
|
## FlaxVisionEncoderDecoderModel
|
|
|
|
[[autodoc]] FlaxVisionEncoderDecoderModel
|
|
- __call__
|
|
- from_encoder_decoder_pretrained
|