* first try * Update modeling_utils.py * Update modeling_utils.py * big refactor * Update modeling_utils.py * style * docstrings and simplify inner workings of configs * remove all trace of _internal * Update modeling_utils.py * fix logic error * Update modeling_utils.py * recursive on config * Update configuration_utils.py * fix * Update configuration_dpt.py * Update configuration_utils.py * Update configuration_utils.py * Update modeling_idefics.py * Update modeling_utils.py * fix for old models * more old models fixup * Update modeling_utils.py * Update configuration_utils.py * Remove outdated test * remove the deepcopy!! 🥵🥵 * Update test_modeling_gpt_bigcode.py * fix qwen dispatch * restrict to only models supporting it * style * switch name * Update modeling_utils.py * Update modeling_utils.py * add tests! * fix * rypo * remove bad copies * fix * Update modeling_utils.py * additional check * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * fix * skip
20 lines
425 B
Python
20 lines
425 B
Python
import torch
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from transformers import PreTrainedModel
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from .custom_configuration import CustomConfig
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class CustomModel(PreTrainedModel):
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config_class = CustomConfig
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def __init__(self, config):
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super().__init__(config)
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self.linear = torch.nn.Linear(config.hidden_size, config.hidden_size)
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def forward(self, x):
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return self.linear(x)
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def _init_weights(self, module):
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pass
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