---
title: rice-vit-large-patch14-560
canonical_url: "https://www.modelscope.cn/models/deepglint/rice-vit-large-patch14-560"
md_url: "https://www.modelscope.cn/models/deepglint/rice-vit-large-patch14-560.md"
repository: deepglint/rice-vit-large-patch14-560
last_updated: 2026-01-19
license: mit
model_type:
  - mlcd
architectures:
  - MLCDVisionModel
library_name:
  - pytorch
  - transformer
  - safetensors
frameworks:
  - pytorch
downloads: 49
stars: 0
---

# rice-vit-large-patch14-560

> rice-vit-large-patch14-560 - deepglint 在 ModelScope 开源的模型。RICE-ViT-L Model Card

deepglint/rice-vit-large-patch14-560 是 ModelScope 魔搭社区上的机器学习模型，采用 mit 许可。

- **Repository**: deepglint/rice-vit-large-patch14-560
- **License**: mit
- **Downloads**: 49
- **Stars**: 0
- **Last updated**: 2026-01-19

Source: https://www.modelscope.cn/models/deepglint/rice-vit-large-patch14-560

---

## RICE-ViT-L Model Card


[[Github]](https://github.com/deepglint/MVT) [[Paper]](https://arxiv.org/abs/2507.20025) 

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6478679d7b370854241b2ad8/Yy09pOusaZ47LofJ27xox.jpeg)

## Installation

```shell
pip install torch transformers
git clone https://github.com/deepglint/unicom
cd unicom/mlcd
```

## Usage

```python
from vit_rope2d_hf import MLCDVisionModel
from transformers import CLIPImageProcessor
from PIL import Image
import requests
import torch

# Load model and processor
model = MLCDVisionModel.from_pretrained("DeepGlint-AI/rice-vit-large-patch14-560")
processor = CLIPImageProcessor.from_pretrained("DeepGlint-AI/rice-vit-large-patch14-560")

# Process single image
url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)
inputs = processor(images=image, return_tensors="pt")

# Get visual features
with torch.no_grad():
    outputs = model(**inputs)
features = outputs.last_hidden_state

print(f"Extracted features shape: {features.shape}")
```