如何自动将Pytorch模型转换为拥抱面模型？

Question

假设我创建了一个pytorch模型：

class Model(nn.Module):
    def __init__(self):
        super(Model, self).__init__()
        
        self.model_1_encoder = RobertaModel.from_pretrained('roberta-base')
        self.model_2_encoder = RobertaModel.from_pretrained('roberta-base')

        self.dropout = nn.Dropout(0.5)
        self.linear_model_1_out = nn.Linear(768, 512)
        self.linear_model_2_out = nn.Linear(768, 512)
    
        self.linear3 = nn.Linear(512, 512)
        self.linear4 = nn.Linear(512, 1)
        
    def forward(self, x):
        question_input_ids, attn_mask, xyz_input_ids, xyz_attention_mask = torch.tensor(x['input_ids']), torch.tensor(x['attention_mask']), torch.tensor(x['xyz_ids']), torch.tensor(x['xyz_mask'])
        model_1_outputs = self.model_1_encoder(question_input_ids, attention_mask=attn_mask)
        model_2_outputs = self.model_2_encoder(xyz_input_ids, attention_mask = xyz_attention_mask)
        model_1_outputs = self.dropout(model_1_outputs[0])
        model_2_outputs = self.dropout(model_2_outputs[0])

        model_2_outputs = torch.sum(model_2_outputs, dim=0) 
        model_2_outputs = torch.unsqueeze(model_2_outputs, 0) 
        model_2_outputs = model_2_outputs.repeat(model_1_outputs.shape[0], 1, 1) 

        model_1_outputs = self.linear_model_1_out(model_1_outputs)
        model_2_outputs = self.linear_model_2_out(model_2_outputs)

        model_1_and_xyz_sum = model_2_outputs + model_1_outputs 
        outputs = self.dropout(model_1_and_xyz_sum)
        outputs = outputs[:,0,:].view(-1,512) 
        outputs = torch.relu(self.linear3(outputs))
        outputs = self.dropout(outputs)
        outputs = torch.relu(self.linear4(outputs))
        return outputs

model = Model()

from this 因此，我知道我需要为Pytorch模型创建一个配置文件，该文件将由模型加载。他们引用了如何向变形金刚添加模型？除其他各种输入和步骤外，我的自定义模型中的每一层。我还找到了 this this 他们的论坛上的问题，引用 this 转换Pytorch模型。

如何自动将我的pytorch模型转换为Hugginface模型，以便我可以使用他们的Trainer类（除了DataCollat​​or等其他功能之外）？

潜在的最佳伪代码：

my_pytorch_model = Model()
my_huggingface_model = Custom_huggingface_Model.load_model(my_pytorch_model)