added

app.py

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+import gradio as gr
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+import torch
+
+# Load your model from Hugging Face
+tokenizer = T5Tokenizer.from_pretrained("https://huggingface.co/quynhthames/vietnamese-math-solver")
+model = T5ForConditionalGeneration.from_pretrained("https://huggingface.co/quynhthames/vietnamese-math-solver")
+
+#Use Cuda if avalible.
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+def solve_math_problem(problem):
+    # Tokenize the input
+    inputs = tokenizer(problem, return_tensors="pt").to(device)
+
+    # Generate the solution
+    outputs = model.generate(**inputs)
+
+    # Decode the output
+    solution = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    return solution
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=solve_math_problem,
+    inputs="text",
+    outputs="text",
+    title="Math Problem Solver",
+    description="Enter a math problem and get the solution."
+)
+
+iface.launch()

requirements.txt

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+gradio
+transformers
+torch