| However, you can still replace - some or all of - the default model configuration attributes with your own if you'd like: | |
| model = DistilBertModel.from_pretrained("distilbert/distilbert-base-uncased", config=my_config) | |
| Load your custom configuration attributes into the model: | |
| from transformers import TFDistilBertModel | |
| my_config = DistilBertConfig.from_pretrained("./your_model_save_path/my_config.json") | |
| tf_model = TFDistilBertModel(my_config) | |
| This creates a model with random values instead of pretrained weights. |