Update app.py

app.py

@@ -3,7 +3,7 @@ import gradio as gr
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2-medium")
+tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2-medium", clean_up_tokenization_spaces=True)
 model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2-medium")
 
 system_prompt = """
@@ -23,8 +23,10 @@ output: Potential widening of the achievement gap if data is not used equitably.
 def generate(text):
     try:
         prompt = system_prompt + f"\ninput: {text}\noutput:"
-        inputs = tokenizer.encode(prompt, return_tensors="pt", return_attention_mask=True)
-        outputs = model.generate(inputs["input_ids"], attention_mask=inputs["attention_mask"], max_length=256)
+        inputs = tokenizer(prompt, return_tensors="pt", return_attention_mask=True)
+        input_ids = inputs["input_ids"].unsqueeze(0)
+        attention_mask = inputs["attention_mask"].unsqueeze(0)
+        outputs = model.generate(input_ids, attention_mask=attention_mask, max_length=256)
         response_text = tokenizer.decode(outputs[0], skip_special_tokens=True).split("output:")[-1].strip()
         return response_text if response_text else "No valid response generated."