testing

modeling_prismatic.py

@@ -429,14 +429,14 @@ class PrismaticForConditionalGeneration(PrismaticPreTrainedModel):
                 f"=> `past_key_values` = {past_key_values is not None}\n"
                 f"=> `use_cache` = {use_cache}"
             )
-
+        print('HUGGINGFACE HELLO')
         # Unpack `language_model_output` and return PrismaticCausalLMOutputWithPast (or tuple if not `return_dict`)
         if not return_dict:
             if output_projector_features and (projected_patch_embeddings is not None):
                 return *language_model_output, projected_patch_embeddings
 
             return language_model_output
-
+        
         return PrismaticCausalLMOutputWithPast(
             loss=language_model_output.loss,
             logits=language_model_output.logits,