README.md

---
license: apache-2.0
---

This is a d-Matrix functional reference of the clip-vit-base-patch32 model.
The reference provides the following functional *configurations*:
  Configuration | Explanation
  :-- | :-- 
  **`BASELINE`** | a reference functionally equivalent to the original model
  **`BASIC`** | all linear algebraic operands quantized to `MXINT8-64`, and all other operations transformed to approximated kernel simulations


### Usage

Install d-Matrix [Dmx_Compressor](https://github.com/d-matrix-ai/dmx-compressor) first.
```sh
pip install dmx_compressor
```

The following is an example model and its usage.

```python
from PIL import Image
import requests

from transformers import CLIPProcessor, CLIPModel
from dmx.compressor.modeling import DmxModel

model = CLIPModel.from_pretrained("d-matrix/clip-vit-base-patch32")
processor = CLIPProcessor.from_pretrained("d-matrix/clip-vit-base-patch32")

url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

inputs = processor(
    text=["a photo of a cat", "a photo of a dog"],
    images=image,
    return_tensors="pt",
    padding=True,
)

model = DmxModel.from_torch(model)
outputs = model(**inputs)
```