format stuff

app.py

@@ -2,26 +2,29 @@ import gradio as gr
 import spaces
 import torch
 import os
-
 from transformers import AutoTokenizer, AutoModelForCausalLM
-from huggingface_hub import login
 
-hf_key = os.environ['HF_TOKEN']
-login(token = hf_key)
+import huggingface_hub
+
+hf_key = os.environ["HF_TOKEN"]
+huggingface_hub.login(token=hf_key)
 
-tokenizer = AutoTokenizer.from_pretrained('bigcode/starcoderbase-3b', use_auth_token=hf_key)
+tokenizer = AutoTokenizer.from_pretrained(
+    "bigcode/starcoderbase-3b", use_auth_token=hf_key
+)
 vardecoder_model = AutoModelForCausalLM.from_pretrained(
-    "ejschwartz/resym-vardecoder",
-    torch_dtype=torch.bfloat16, device_map='auto'
+    "ejschwartz/resym-vardecoder", torch_dtype=torch.bfloat16, device_map="auto"
 )
 
 zero = torch.Tensor([0]).cuda()
-print(zero.device) # <-- 'cpu' 🤔
+print(zero.device)  # <-- 'cpu' 🤔
+
 
 @spaces.GPU
 def greet(n):
-    print(zero.device) # <-- 'cuda:0' 🤗
+    print(zero.device)  # <-- 'cuda:0' 🤗
     return f"Hello {zero + n} Tensor"
 
+
 demo = gr.Interface(fn=greet, inputs=gr.Number(), outputs=gr.Text())
 demo.launch()