from transformers import AutoModelForCausalLM, AutoProcessor
from PIL import Image

# Load model and processor
model = AutoModelForCausalLM.from_pretrained(
    "YOUR_USERNAME/OCR-int4-merged",
    trust_remote_code=True
)
processor = AutoProcessor.from_pretrained(
    "YOUR_USERNAME/OCR-int4-merged",
    trust_remote_code=True
)

# Process image
image = Image.open("document.jpg")
inputs = processor(images=image, return_tensors="pt")

# Generate OCR output
outputs = model.generate(**inputs, max_new_tokens=512)
text = processor.decode(outputs[0], skip_special_tokens=True)
print(text)

Notes

This model was created by:

Quantizing the original DeepSeek-OCR to INT4
Dequantizing back to full precision
Merging into a standard model format

The process allows for efficient storage and distribution while maintaining full model capabilities.

SamMikaelson/ocr_random_merged

DeepSeek-OCR INT4 Merged Model

Model Details

Usage

Notes

SamMikaelson/
ocr_random_merged