rename gpt nano -> gpt micro

app.py

@@ -26,13 +26,13 @@ wavenet_weights_path = huggingface_hub.hf_hub_download(
     "jefsnacker/surname_generator",
     "wavenet_weights.pt")
 
-gpt_nano_config_path = huggingface_hub.hf_hub_download(
+gpt_micro_config_path = huggingface_hub.hf_hub_download(
     "jefsnacker/surname_generator",
-    "gpt_config.yaml")
+    "micro_gpt_config.yaml")
 
-gpt_nano_weights_path = huggingface_hub.hf_hub_download(
+gpt_micro_weights_path = huggingface_hub.hf_hub_download(
     "jefsnacker/surname_generator",
-    "gpt_weights.pt")
+    "micro_gpt_weights.pt")
 
 with open(mlp_config_path, 'r') as file:
     mlp_config = yaml.safe_load(file)
@@ -40,8 +40,8 @@ with open(mlp_config_path, 'r') as file:
 with open(wavenet_config_path, 'r') as file:
     wavenet_config = yaml.safe_load(file)
     
-with open(gpt_nano_config_path, 'r') as file:
-    gpt_nano_config = yaml.safe_load(file)
+with open(gpt_micro_config_path, 'r') as file:
+    gpt_micro_config = yaml.safe_load(file)
 
 ##################################################################################
 ## MLP
@@ -310,9 +310,9 @@ class GPT(nn.Module):
         probs = F.softmax(logits[:,-1,:], dim=1)
         return torch.multinomial(probs, num_samples=1).item()
 
-gpt_nano = GPT(gpt_nano_config)
-gpt_nano.load_state_dict(torch.load(gpt_nano_weights_path))
-gpt_nano.eval()
+gpt_micro = GPT(gpt_micro_config)
+gpt_micro.load_state_dict(torch.load(gpt_micro_weights_path))
+gpt_micro.eval()
 
 ##################################################################################
 ## Gradio App
@@ -325,9 +325,9 @@ def generate_names(name_start, number_of_names, model):
     elif model == "WaveNet":
         stoi = wavenet_config['stoi']
         window = wavenet_config['window']
-    elif model == "GPT Nano":
-        stoi = gpt_nano_config['stoi']
-        window = gpt_nano_config['window']
+    elif model == "GPT Micro":
+        stoi = gpt_micro_config['stoi']
+        window = gpt_micro_config['window']
     else:
         raise Exception("Model not selected")
         
@@ -350,8 +350,8 @@ def generate_names(name_start, number_of_names, model):
                 ix = mlp.sample_char(x)
             elif model == "WaveNet":
                 ix = wavenet.sample_char(x)
-            elif model == "GPT Nano":
-                ix = gpt_nano.sample_char(x)
+            elif model == "GPT Micro":
+                ix = gpt_micro.sample_char(x)
             else:
                 raise Exception("Model not selected")
                 
@@ -370,7 +370,7 @@ demo = gr.Interface(
     inputs=[
         gr.Textbox(placeholder="Start name with..."),
         gr.Number(value=5),
-        gr.Dropdown(["MLP", "WaveNet", "GPT Nano"], value="GPT Nano"),
+        gr.Dropdown(["MLP", "WaveNet", "GPT Micro"], value="GPT Micro"),
     ],
     outputs="text",
 )