feat: configure for ZeroGPU with A100

README.md

@@ -4,18 +4,19 @@ emoji: 🧮
 colorFrom: blue
 colorTo: green
 sdk: gradio
-sdk_version: 4.8.0
+sdk_version: 4.44.1
 app_file: app.py
 pinned: false
 hardware:
-  accelerator: a100
-  gpu: true
+  zerogpu: true
+  memory: 16
 python_packages:
   - "torch>=2.0.0"
   - "transformers>=4.30.0"
   - "accelerate>=0.20.0"
   - "peft==0.5.0"
   - "numpy>=1.21.0"
+  - "spaces>=0.1.0"
 ---
 
 # Mathematics Derivative Solver V2
@@ -29,7 +30,7 @@ This Space demonstrates our fine-tuned math model for solving derivatives. We us
 
 - Step-by-step derivative solutions
 - LaTeX notation support
-- A100 GPU acceleration
+- A100 GPU acceleration via ZeroGPU
 - Float16 precision for efficient inference
 
 ## Supported Functions

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from peft import PeftModel
+import spaces
 
 # Model configurations
 BASE_MODEL = "HuggingFaceTB/SmolLM2-1.7B-Instruct"  # Base model
@@ -36,9 +37,10 @@ def format_prompt(function: str) -> str:
 Function: {function}
 The derivative of this function is:"""
 
+@spaces.GPU
 def generate_derivative(function: str, max_length: int = 100) -> str:
     """Generate derivative for a given function"""
-    # Format the prompt
+    # Format prompt
     prompt = format_prompt(function)
     
     # Tokenize
@@ -61,6 +63,7 @@ def generate_derivative(function: str, max_length: int = 100) -> str:
     
     return derivative
 
+@spaces.GPU
 def solve_derivative(function: str) -> str:
     """Solve derivative and format output"""
     if not function:

requirements.txt

@@ -4,3 +4,4 @@ accelerate>=0.20.0
 peft==0.5.0
 gradio==4.44.1
 numpy>=1.21.0
+spaces>=0.1.0