Create app.py

app.py

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+
+import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
+
+from functools import lru_cache
+
+# Define models
+BASE_MODEL = "deepseek-ai/deepseek-math-7b-rl"
+FINETUNED_MODEL = "LaibaIrfan/emoji_math"
+
+# Load tokenizer and model
+@lru_cache()
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained(FINETUNED_MODEL)
+
+    base_model = AutoModelForCausalLM.from_pretrained(
+        BASE_MODEL,
+        torch_dtype=torch.float16,  # Use float16 for efficiency
+        device_map="auto",          # Auto-assign device (GPU if available)
+        load_in_8bit=True           # Reduce memory usage (slightly increases inference time)
+    )
+
+    model = PeftModel.from_pretrained(
+        base_model,
+        FINETUNED_MODEL,
+        device_map="auto" 
+    )
+
+    return tokenizer, model
+
+# Load the model
+tokenizer, model = load_model()
+
+# Function to generate the result
+def generate_result(incorrect_math):
+    input_text = f"Incorrect: {incorrect_math}\nCorrect:"
+
+    # Move input to GPU
+    inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
+
+    # Generate output on GPU
+    output = model.generate(**inputs, max_length=200)
+
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=generate_result,
+    inputs="text",
+    outputs="text",
+    title="Emoji Math Solver 🧮",
+    description="Enter an emoji-based math equation, and the model will generate the correct answer!"
+)
+
+iface.launch(debug=True, share=True, inline=True)
+
+# Function to generate result
+def generate_result(incorrect_math):
+    input_text = f"Incorrect: {incorrect_math}\nCorrect:"
+    inputs = tokenizer(input_text, return_tensors="pt").to("cuda")  # Use GPU if available
+    output = model.generate(**inputs, max_length=200)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=generate_result,
+    inputs="text",
+    outputs="text",
+    title="Emoji Math Solver 🧮",
+    description="Enter an emoji-based math equation, and the model will generate the correct answer!"
+)
+
+iface.launch(share=True)