| from transformers import PretrainedConfig | |
| class EmuruConfig(PretrainedConfig): | |
| model_type = "emuru" # Unique identifier for your model | |
| def __init__(self, | |
| t5_config='google-t5/t5-large', | |
| vae_config='blowing-up-groundhogs/emuru_vae', | |
| tokenizer_config='google/byt5-small', | |
| slices_per_query=1, | |
| vae_channels=1, | |
| **kwargs): | |
| super().__init__(**kwargs) | |
| self.t5_config = t5_config | |
| self.vae_config = vae_config | |
| self.tokenizer_config = tokenizer_config | |
| self.slices_per_query = slices_per_query | |
| self.vae_channels = vae_channels | |