Update app.py

app.py

@@ -1,13 +1,19 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# Load your text generation model from Hugging Face
-model_name = "curiouscurrent/omnicode"
-text_generator = pipeline("text-generation", model=model_name)
+# Load your text generation model from Hugging Face using its identifier
+model_identifier = "your-model-name-on-hugging-face"
+model = AutoModelForCausalLM.from_pretrained(model_identifier)
+tokenizer = AutoTokenizer.from_pretrained(model_identifier)
 
 def generate_response(input_prompt):
+    # Tokenize input prompt
+    input_ids = tokenizer.encode(input_prompt, return_tensors="pt", max_length=512, truncation=True)
+    
     # Generate response
-    response = text_generator(input_prompt, max_length=100)[0]['generated_text']
+    output_ids = model.generate(input_ids, max_length=100, num_return_sequences=1)
+    response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    
     return response
 
 # Create Gradio interface
@@ -19,6 +25,6 @@ gr.Interface(
     inputs=input_prompt,
     outputs=output_text,
     title="OmniCode",
-    description="Multi Programming coding assistant.",
+    description="Multi programming coding assistant",
     theme="compact"
 ).launch()