# DinoV3 Vision Transformer Huge (INT8 Quantized)

INT8 quantized version of `facebook/dinov3-vith16plus-pretrain-lvd1689m` using BitsAndBytes.

## Model Details

- **Base Model**: DinoV3 Vision Transformer Huge (840M parameters)
- **Quantization**: INT8 weight-only quantization via BitsAndBytes
- **Size**: ~845MB (from ~1.7GB original)
- **Compression**: ~2x size reduction
- **Accuracy Loss**: <1% typical

## Usage

```python
from transformers import AutoModel, BitsAndBytesConfig

# Load the INT8 quantized model
model = AutoModel.from_pretrained(
    "Omdano/INT8-H16P",
    trust_remote_code=True,
    quantization_config=BitsAndBytesConfig(load_in_8bit=True),
    device_map="auto"
)

# Use for feature extraction or classification
outputs = model(pixel_values=inputs)
```

## Benefits

- **2x smaller** than full precision model
- **Faster inference** on GPU
- **Same API** as original DinoV3
- **Minimal accuracy loss** (<1%)

## Requirements

```bash
pip install transformers bitsandbytes torch
```

## Original Model

Based on [facebook/dinov3-vith16plus-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vith16plus-pretrain-lvd1689m)

## License

Apache 2.0 (same as original DinoV3)