Create app.py

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "nvidia/OpenReasoning-Nemotron-1.5B"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model.to(device)
+
+def chat_api(prompt, max_new_tokens=200, temperature=0.7):
+    inputs = tokenizer(prompt, return_tensors="pt").to(device)
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=max_new_tokens,
+        temperature=temperature,
+        do_sample=True
+    )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+demo = gr.Interface(
+    fn=chat_api,
+    inputs=[
+        gr.Textbox(label="Prompt", placeholder="Ask me anything..."),
+        gr.Slider(50, 512, value=200, step=10, label="Max Tokens"),
+        gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
+    ],
+    outputs="text",
+    title="OpenReasoning Nemotron-1.5B API",
+    description="Public Hugging Face Space that runs NVIDIA's Nemotron-1.5B model."
+)
+
+demo.launch()