Update app.py

app.py

@@ -12,10 +12,10 @@ print(f'[INFO] Using device: {device}')
 token = os.environ['TOKEN']
 
 # Load the pretrained model and tokenizer
-MODEL_NAME = "atlasia/Al-Atlas-LLM" # "BounharAbdelaziz/Al-Atlas-LLM-0.5B" #"atlasia/Al-Atlas-LLM"
+MODEL_NAME = "BounharAbdelaziz/Al-Atlas-LLM-0.5B" # "atlasia/Al-Atlas-LLM-mid-training" # "BounharAbdelaziz/Al-Atlas-LLM-0.5B" #"atlasia/Al-Atlas-LLM"
 
-tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=token)
-model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, token=token).to(device)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) # , token=token
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).to(device)
 
 # Predefined examples
 examples = [
@@ -52,9 +52,9 @@ if __name__ == "__main__":
             fn=generate_text,
             inputs=[
                 gr.Textbox(label="Prompt: دخل النص بالدارجة"),
-                gr.Slider(50, 4096, value=256, label="Max Length"),
-                gr.Slider(0.1, 1.5, value=0.7, label="Temperature"),
-                gr.Slider(0.1, 1.0, value=0.9, label="Top-p"),
+                gr.Slider(8, 4096, value=256, label="Max Length"),
+                gr.Slider(0.0, 2, value=0.7, label="Temperature"),
+                gr.Slider(0.0, 1.0, value=0.9, label="Top-p"),
                 gr.Slider(1, 10000, value=150, label="Top-k"),
                 gr.Slider(1, 20, value=8, label="Number of Beams"),
                 gr.Slider(0.0, 100.0, value=1.5, label="Repetition Penalty"),