Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "DiscoResearch/DiscoLM_German_7b_v1"
+model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+
+def generate_answer(question):
+    inputs = tokenizer.encode("Question: " + question, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=2000, num_return_sequences=1, do_sample=True)
+    answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return answer
+
+iface = gr.Interface(
+    fn=generate_answer,
+    inputs="text",
+    outputs="text",
+    title="The Art of Prompt Engineering",
+    description="Definiere deine Prompt, am besten auf Deutsch",
+)
+
+iface.launch(share=True)  # Deploy the interface