create app.py with

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+import re
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Modell und Tokenizer laden
+# distilgpt2 is only 80MB -> no inference model, thus add prompt_prefix or train
+tokenizer = AutoTokenizer.from_pretrained("distilgpt2")
+model = AutoModelForCausalLM.from_pretrained("distilgpt2")
+
+# conversion method
+def text_to_emoji(input_text):
+    # Eingabetext bereinigen (optional)
+    cleaned_text = re.sub(r"[.,!?;:]", "", input_text)
+
+    # Pattern-based prompt with data from prompt_prefix
+    prompt = "(\n" + "".join(f'"{line}\\n"\n' for line in train_data[0:3]) + f"\"{input_text} →\"" + ")"
+    
+    # Tokenisierung und Generation
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=10,
+        do_sample=True,
+        temperature=0.9,
+        top_k=50,
+        pad_token_id=tokenizer.eos_token_id  # Prevents warning
+    )
+
+    # Decodieren
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Nur den generierten Teil nach dem letzten "→"
+    emoji_part = generated_text.split("→")[-1].strip().split("\n")[0]
+
+    return emoji_part
+    
+# Gradio UI
+iface = gr.Interface(
+    fn=text_to_emoji,
+    inputs=gr.Textbox(lines=2, placeholder="Enter a sentence..."),
+    outputs="text",
+    title="AI-Powered Emoji Translator",
+    description="Enter a sentence, and the AI will transform it into an emoji-version 🥳"
+)
+
+iface.launch()