Cleanup: set shared.model_name only once

extensions/openai/models.py

@@ -55,7 +55,6 @@ def _load_model(data):
                 setattr(shared.args, k, args[k])
 
     shared.model, shared.tokenizer = load_model(model_name)
-    shared.model_name = model_name
 
     # Update shared.settings with custom generation defaults
     if settings:

modules/evaluate.py

@@ -69,9 +69,8 @@ def calculate_perplexity(models, input_dataset, stride, _max_length):
                 model_settings = get_model_metadata(model)
                 shared.settings.update({k: v for k, v in model_settings.items() if k in shared.settings})  # hijacking the interface defaults
                 update_model_parameters(model_settings)  # hijacking the command-line arguments
-                shared.model_name = model
                 unload_model()
-                shared.model, shared.tokenizer = load_model(shared.model_name)
+                shared.model, shared.tokenizer = load_model(model)
             except:
                 cumulative_log += f"Failed to load `{model}`. Moving on.\n\n"
                 yield cumulative_log

modules/models.py

@@ -58,6 +58,7 @@ def load_model(model_name, loader=None):
     t0 = time.time()
 
     shared.is_seq2seq = False
+    shared.model_name = model_name
     load_func_map = {
         'Transformers': huggingface_loader,
         'AutoGPTQ': AutoGPTQ_loader,

modules/ui_model_menu.py

@@ -203,10 +203,9 @@ def load_model_wrapper(selected_model, loader, autoload=False):
     else:
         try:
             yield f"Loading `{selected_model}`..."
-            shared.model_name = selected_model
             unload_model()
             if selected_model != '':
-                shared.model, shared.tokenizer = load_model(shared.model_name, loader)
+                shared.model, shared.tokenizer = load_model(selected_model, loader)
 
             if shared.model is not None:
                 output = f"Successfully loaded `{selected_model}`."