Create app.py

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the pretrained model and tokenizer
+MODEL_NAME = "atlasia/Al-Atlas-LLM"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map="auto")
+
+def generate_text(prompt, max_length=256, temperature=0.7, top_p=0.9, top_k=150, repetition_penalty=1.5):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    output = model.generate(
+        **inputs, 
+        max_length=max_length, 
+        temperature=temperature, 
+        top_p=top_p, 
+        do_sample=True,
+        repetition_penalty=repetition_penalty,
+        num_beams=8,
+        top_p= top_p,
+        top_k= top_k,
+        early_stopping = True,
+    )
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=generate_text,
+    inputs=[
+        gr.Textbox(label="Prompt: دخل النص بالدارجة"),
+        gr.Slider(50, 500, 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(1, 10000, value=150, label="Top-k"),
+        gr.Slider(0.0, 100.0, value=1.5, label="Repetition Penalty"),
+    ],
+    outputs=gr.Textbox(label="Generated Text in Moroccan Darija"),
+    title="Moroccan Darija LLM",
+    description="Enter a prompt and get AI-generated text using our pretrained LLM on Moroccan Darija."
+)
+
+if __name__ == "__main__":
+    iface.launch()