Improved logging

app.py

@@ -4,8 +4,7 @@ from transformers import BloomTokenizerFast, BloomForCausalLM
 tokenizer = BloomTokenizerFast.from_pretrained("bigscience/bloom-560m")
 # https://huggingface.co/blog/how-to-generate
 
-def generate(text, temp=0.7):
-    print(temp)
+def generate(text, temp=0.7, logging=True):
     input_ids = tokenizer.encode(text, return_tensors='pt')
     output = model.generate(
         input_ids, 
@@ -17,7 +16,10 @@ def generate(text, temp=0.7):
         repetition_penalty=1.2,
         min_length=len(text)+1
     )
-    return tokenizer.decode(output[0], skip_special_tokens=True)
+    decoded = tokenizer.decode(output[0], skip_special_tokens=True)
+    if logging:
+        print(f"\n\n{'-'*100}\nInput:  {text}\nOutput: {decoded}\nTemp:   {temp}")
+    return decoded
 
 description = "Generate Titles for the Vice Youtube Channel"
 title = "Vice Headlines"