Create app.py

app.py

@@ -0,0 +1,28 @@
+import spaces
+import gradio as gr
+from cartesia_pytorch import ReneLMHeadModel
+from transformers import AutoTokenizer
+
+# Load model and tokenizer
+model = ReneLMHeadModel.from_pretrained("cartesia-ai/Rene-v0.1-1.3b-pytorch").half().cuda()
+tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-1B-hf")
+
+# Define the function to generate text
+@spaces.GPU(duration=120)
+def generate_text(input_text):
+    inputs = tokenizer([input_text], return_tensors="pt")
+    outputs = model.generate(inputs.input_ids.cuda(), max_length=50, top_k=100, top_p=0.99)
+    out_message = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
+    return out_message
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=generate_text, 
+    inputs="text", 
+    outputs="text",
+    title="ReneLM Text Generator",
+    description="Generate text using ReneLMHeadModel from a prompt."
+)
+
+# Launch the Gradio app
+interface.launch()