Unload and reload models on request

server.py

@@ -63,6 +63,18 @@ def load_model_wrapper(selected_model):
 
     return selected_model
 
+def reload_model():
+    if not shared.args.cpu:
+        gc.collect()
+        torch.cuda.empty_cache()
+    shared.model, shared.tokenizer = load_model(shared.model_name)
+
+def unload_model():
+    shared.model = shared.tokenizer = None
+    if not shared.args.cpu:
+        gc.collect()
+        torch.cuda.empty_cache()
+
 def load_lora_wrapper(selected_lora):
     shared.lora_name = selected_lora
     default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')]
@@ -126,6 +138,9 @@ def create_model_and_preset_menus():
             with gr.Row():
                 shared.gradio['preset_menu'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
                 ui.create_refresh_button(shared.gradio['preset_menu'], lambda : None, lambda : {'choices': get_available_presets()}, 'refresh-button')
+    with gr.Row():
+        shared.gradio['unload_model'] = gr.Button(value='Unload model to free VRAM', elem_id="unload_model")
+        shared.gradio['reload_model'] = gr.Button(value='Reload the model into VRAM', elem_id="reload_model")
 
 def create_settings_menus(default_preset):
     generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', return_dict=True)
@@ -180,6 +195,8 @@ def create_settings_menus(default_preset):
             shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip'])
 
     shared.gradio['model_menu'].change(load_model_wrapper, [shared.gradio['model_menu']], [shared.gradio['model_menu']], show_progress=True)
+    shared.gradio['unload_model'].click(fn=unload_model,inputs=[],outputs=[])    
+    shared.gradio['reload_model'].click(fn=reload_model,inputs=[],outputs=[])
     shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio[k] for k in ['preset_menu_mirror', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
     shared.gradio['preset_menu_mirror'].change(load_preset_values, [shared.gradio['preset_menu_mirror']], [shared.gradio[k] for k in ['preset_menu', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
     shared.gradio['lora_menu'].change(load_lora_wrapper, [shared.gradio['lora_menu']], [shared.gradio['lora_menu'], shared.gradio['textbox']], show_progress=True)