Update app.py

app.py

@@ -32,23 +32,11 @@ available_models = ["0Tick/e621TagAutocomplete","0Tick/danbooruTagAutocomplete"]
 current = Model()
 job_count = 1
 
-base_dir = scripts.basedir()
-models_dir = os.path.join(base_dir, "models")
-
 
 def device():
     return devices.cpu
 
 
-
-def get_model_path(name):
-    dirname = os.path.join(models_dir, name)
-    if not os.path.isdir(dirname):
-        return name
-
-    return dirname
-
-
 def generate_batch(input_ids, min_length, max_length, num_beams, temperature, repetition_penalty, length_penalty, sampling_mode, top_k, top_p):
     top_p = float(top_p) if sampling_mode == 'Top P' else None
     top_k = int(top_k) if sampling_mode == 'Top K' else None
@@ -87,7 +75,7 @@ def generate(id_task, model_name, batch_count, batch_size, text, *args):
         current.name = None
 
         if model_name != 'None':
-            path = get_model_path(model_name)
+            path = model_name
             current.tokenizer = transformers.AutoTokenizer.from_pretrained(path)
             current.model = transformers.AutoModelForCausalLM.from_pretrained(path)
             current.name = model_name
@@ -126,9 +114,6 @@ def generate(id_task, model_name, batch_count, batch_size, text, *args):
     return markup, ''
 
 
-
-list_available_models()
-
 with gr.Blocks(analytics_enabled=False) as space:
     with gr.Row():
         with gr.Column(scale=80):