Create README.md

README.md

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+---
+license: mit
+pipeline_tag: image-feature-extraction
+---
+## RICE-ViT-L Model Card
+
+
+![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}")
+```
+
+
+```