Update modeling_mplug_owl2.py

modeling_mplug_owl2.py

@@ -358,7 +358,7 @@ class MPLUGOwl2LlamaForCausalLM(LlamaForCausalLM, MPLUGOwl2MetaForCausalLM):
             image_tensor = self.image_processor.preprocess(images, return_tensors='pt')['pixel_values'].half().to(self.device)
             
             with torch.inference_mode():
-                output_logits = self.model(input_ids, images=image_tensor)["logits"][:, -1, self.preferential_ids_]
+                output_logits = self(input_ids, images=image_tensor)["logits"][:, -1, self.preferential_ids_]
                 output_logits = output_logits.cpu().detach().numpy() / 100
                 print(output_logits)
                 probabilities.append(np.dot(softmax(output_logits),  self.weight_tensor))