| import torch | |
| import torch.nn as nn | |
| class BeastModel(nn.Module): | |
| def __init__(self, config): | |
| super().__init__() | |
| self.linear = nn.Linear(config.hidden_size, 1) | |
| self.sigmoid = nn.Sigmoid() | |
| def forward(self, input_ids=None, **kwargs): | |
| if input_ids is not None: | |
| x = input_ids.sum(dim=1, keepdim=True).float() | |
| out = self.linear(x) | |
| return self.sigmoid(out) | |
| return None | |