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craffel avatar craffel commented on June 24, 2024

When one calls model.finetune as is done in the colab, the operative gin config file which resides in the pretrained model directly is automatically loaded.
https://github.com/google-research/text-to-text-transfer-transformer/blob/master/t5/models/mtf_model.py#L308
Parsing this config file provides values for things like make_layer_stack. When using model.train, there is no pre-trained model directory so there is no operative config to look at. One option would be to decide on a model you want to use and load the operative config for that file, e.g. for the Base model

    import gin
    with gin.unlock_config():
      gin.parse_config_file("gs://t5-data/pretrained_models/base/operative_config.gin")

Note that you still may need to provide or modify other gin parameters.

from text-to-text-transfer-transformer.

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