Update app.py

app.py

@@ -1,3 +1,28 @@
+import os
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Setze das Cache-Verzeichnis
+os.environ['TRANSFORMERS_CACHE'] = '/path/to/custom/cache/directory'
+
+model_name = "Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Funktion zur Textgenerierung definieren
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"], max_length=100)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
 import gradio as gr
 
-gr.load("models/cognitivecomputations/Wizard-Vicuna-30B-Uncensored").launch()
+# Gradio-Interface erstellen
+iface = gr.Interface(
+    fn=generate_text,
+    inputs="text",
+    outputs="text",
+    title="WizardLM Uncensored SuperCOT StoryTelling"
+)
+
+# Interface mit öffentlichem Link starten
+iface.launch(share=True)