Update app.py

app.py

@@ -1,14 +1,30 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForCausalLM , GenerationConfig
+
+
+generation_config = GenerationConfig(
+    penalty_alpha=0.6,
+    do_sample = True,
+    top_k=5,
+    temperature=0.5,
+    repetition_penalty=1.2,
+    max_new_tokens=100,
+    pad_token_id=tokenizer.eos_token_id
+)
+
 tokenizer = AutoTokenizer.from_pretrained("truongghieu/deci-finetuned", trust_remote_code=True)
 model = AutoModelForCausalLM.from_pretrained("truongghieu/deci-finetuned", trust_remote_code=True)
 
+
+
+
 # Define a function that takes a text input and generates a text output
 def generate_text(text):
-  input_ids = tokenizer.encode(text, return_tensors="pt")
-  output_ids = model.generate(input_ids, max_length=200)
-  output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
-  return output_text
+    input_text = f"###Instruction: {text}\n###Response:"
+    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+    output_ids = model.generate(input_ids, generation_config=generation_config)
+    output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    return output_text
 
 iface = gr.Interface(fn=generate_text, inputs="text", outputs="text")
 iface.launch()