Upgrade GPU to L40S

app.py

@@ -282,7 +282,7 @@ def start_training(
         shutil.copy(script_location + "/requirements.autotrain", dataset_folder + "/requirements.txt")
         # command to run autotrain spacerunner
         cmd = f"autotrain spacerunner --project-name {slugged_lora_name} --script-path {dataset_folder}"
-        cmd += f" --username {profile.username} --token {oauth_token.token} --backend spaces-l4x1"
+        cmd += f" --username {profile.username} --token {oauth_token.token} --backend spaces-l40sx1"
         outcome = subprocess.run(cmd.split())
         if outcome.returncode == 0:
             return f"""# Your training has started. 
@@ -311,11 +311,11 @@ def swap_visibilty(profile: Union[gr.OAuthProfile, None]):
 def update_pricing(steps, oauth_token: Union[gr.OAuthToken, None]):
     if(oauth_token and is_spaces):
         user = whoami(oauth_token.token)
-        seconds_per_iteration = 7.54
+        seconds_per_iteration = 2.00
         total_seconds = (steps * seconds_per_iteration) + 240
-        cost_per_second = 0.80/60/60
+        cost_per_second = 1.80/60/60
         cost = round(cost_per_second * total_seconds, 2)
-        cost_preview = f'''To train this LoRA, a paid L4 GPU will be hooked under the hood during training and then removed once finished.
+        cost_preview = f'''To train this LoRA, a paid L40S GPU will be hooked under the hood during training and then removed once finished.
         ### Estimated to cost <b>< US$ {str(cost)}</b> for {round(int(total_seconds)/60, 2)} minutes with your current train settings <small>({int(steps)} iterations at {seconds_per_iteration}s/it)</small>'''
         if(user["canPay"]):
             return gr.update(visible=True), cost_preview, gr.update(visible=False), gr.update(visible=True)