Upload app.py

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+import gc
+import torch
+
+def clear_memory():
+    gc.collect()
+    torch.cuda.empty_cache()
+
+model_name = "GIGAParviz/Firooze_test"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+model = model.to("cpu")
+
+pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=512)
+
+def generate_response(prompt):
+    clear_memory() 
+    instruction = f"### Instruction:\n{prompt}\n\n### Response:\n"
+    result = pipe(instruction)
+
+    return result[0]['generated_text'][len(instruction):]
+
+with gr.Blocks() as demo:
+    gr.Markdown("<h1 style='text-align: center;'>🔮 Persian LLM made by A.M.Parviz</h1>")
+
+    prompt_input = gr.Textbox(label="Enter Prompt", placeholder="Type your prompt here...", lines=2)
+    
+    generate_button = gr.Button("Generate Response")
+    
+    response_output = gr.Textbox(label="Generated Response", lines=5)
+    
+    generate_button.click(fn=generate_response, inputs=prompt_input, outputs=response_output)
+    
+    clear_button = gr.ClearButton([prompt_input, response_output])
+
+demo.launch()