Upload modeling_InternLM_XComposer.py

modeling_InternLM_XComposer.py

@@ -119,17 +119,13 @@ class InternLMXComposerForCausalLM(PreTrainedModel):
                      vision_width,
                      cross_attention_freq=2,
                      pretrain=True):
-        encoder_config = BertConfig.from_pretrained("bert-base-uncased")
+        encoder_config = BertConfig()
         encoder_config.encoder_width = vision_width
         # insert cross-attention layer every other block
         encoder_config.add_cross_attention = True
         encoder_config.cross_attention_freq = cross_attention_freq
         encoder_config.query_length = num_query_token
-        if pretrain:
-            Qformer = BertLMHeadModel.from_pretrained("bert-base-uncased",
-                                                      config=encoder_config)
-        else:
-            Qformer = BertLMHeadModel(config=encoder_config)
+        Qformer = BertLMHeadModel(config=encoder_config)
         query_tokens = nn.Parameter(
             torch.zeros(1, num_query_token, encoder_config.hidden_size))
         query_tokens.data.normal_(mean=0.0,