chunked/content_aware_chunking/_custom_models/chunk_17.txt

The configuration file contains the code for ResnetConfig and the modeling file
contains the code of ResnetModel and ResnetModelForImageClassification.
.
└── resnet_model
    ├── __init__.py
    ├── configuration_resnet.py
    └── modeling_resnet.py
The __init__.py can be empty, it's just there so that Python detects resnet_model can be use as a module.

If copying a modeling files from the library, you will need to replace all the relative imports at the top of the file
to import from the transformers package.

Note that you can re-use (or subclass) an existing configuration/model.
To share your model with the community, follow those steps: first import the ResNet model and config from the newly
created files:
py
from resnet_model.configuration_resnet import ResnetConfig
from resnet_model.modeling_resnet import ResnetModel, ResnetModelForImageClassification
Then you have to tell the library you want to copy the code files of those objects when using the save_pretrained
method and properly register them with a given Auto class (especially for models), just run:
py
ResnetConfig.register_for_auto_class()
ResnetModel.register_for_auto_class("AutoModel")
ResnetModelForImageClassification.register_for_auto_class("AutoModelForImageClassification")
Note that there is no need to specify an auto class for the configuration (there is only one auto class for them,
[AutoConfig]) but it's different for models.