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from transformers import PreTrainedModel
from .configuration_ss4m import SimpleStories4MConfig
from .nano_gpt_model import NanoGPT
class SimpleStories4MModel(PreTrainedModel):
config_class = SimpleStories4MConfig
def __init__(self, config):
super().__init__(config)
hyperparameters = {
"vocab_size": config.vocab_size,
"block_size": config.block_size,
"n_embed": config.n_embed,
"n_heads": config.n_heads,
"n_layers": config.n_layers,
"dropout": config.dropout,
}
self.model = NanoGPT(hyperparameters)
def forward(self, tensor, targets=None):
return self.model(tensor, targets) |