test_minimal.py

from transformers import AutoModel, AutoTokenizer
import torch
import os
from PIL import Image

model_name = 'deepseek-ai/DeepSeek-OCR-2'

def test_inference():
    print(f"Loading tokenizer for {model_name}...")
    tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)

    print(f"Loading model for {model_name}...")
    # Load model on CPU
    model = AutoModel.from_pretrained(
        model_name, 
        trust_remote_code=True, 
        use_safetensors=True
    )
    
    # Check if loaded
    print("Model loaded successfully.")
    print(f"Model type: {type(model)}")
    
    # Test simple tokenization
    inputs = tokenizer("Hello", return_tensors="pt")
    print("Tokenizer test: Success")
    
    print("DeepSeek-OCR-2 is ready for use.")

if __name__ == "__main__":
    test_inference()