added app file

app.py

@@ -0,0 +1,48 @@
+import gradio as gr
+from threading import Thread
+from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer
+
+model_id = "KennethTM/gpt-neo-1.3B-danish"
+peft_model_id = "KennethTM/gpt-neo-1.3B-danish-lora-r64-a128"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+model.load_adapter(peft_model_id)
+model.eval()
+
+def run_generation(user_text):
+    model_inputs = tokenizer(user_text, return_tensors="pt")
+
+    streamer = TextIteratorStreamer(tokenizer, skip_prompt=False, skip_special_tokens=True)
+    
+    generate_kwargs = dict(
+        inputs = model_inputs.input_ids,
+        attention_mask = model_inputs.attention_mask,
+        streamer = streamer,
+        max_new_tokens = 20,
+        penalty_alpha = 0.6,
+        top_k = 4,
+    )
+
+    t = Thread(target=model.generate, kwargs=generate_kwargs)
+    t.start()
+
+    model_output = ""
+    for new_text in streamer:
+        model_output += new_text
+        yield model_output
+    
+    return model_output
+
+with gr.Blocks() as demo:
+
+    gr.Markdown("# Auto-completion med dansk sprogmodel")
+    gr.Markdown("## Tryk 'Kør' eller 'SHIFT+ENTER' for auto-completion!")
+    textbox = gr.Textbox(placeholder="Skriv her...", lines=10)
+    btn = gr.Button("Kør")
+    btn.click(run_generation, textbox, textbox)
+    textbox.submit(run_generation, textbox, textbox)
+    gr.Markdown("## Om")
+    gr.Markdown("*Dansk sprogmodel (KennethTM/gpt-neo-1.3B-danish) fin-tunet yderligere med PEFT på udvalgte tekster om natur og miljø*")
+
+demo.queue().launch()