Update README.md

README.md

@@ -1,48 +1,46 @@
----
-license: mit
-tags:
-- clip
-- feature-extraction
----
-
-# DGTRS-CLIP-ViT-L-14
-
-This is the DGTRS-CLIP-ViT-L-14 model. It can be used for a variety of tasks, including zero-shot image classification and text-image retrieval.
-
-This model is compatible with both the `transformers` and `diffusers` libraries.
-
-## How to use
-
-### With `transformers`
-
-```python
-from transformers import CLIPProcessor, CLIPModel
-
-model = CLIPModel.from_pretrained("BiliSakura/DGTRS-CLIP-ViT-L-14")
-processor = CLIPProcessor.from_pretrained("BiliSakura/DGTRS-CLIP-ViT-L-14")
-
-# Your code here to use the model for image-text similarity, zero-shot classification, etc.
-```
-
-### With `diffusers`
-
-This model's text encoder can be used with Stable Diffusion:
-
-```python
-# Your code here to use the text encoder with a diffusion model.
-```
-
-## Citation
-
-If you use this model in your research, please cite the original paper:
-
-```
-@misc{chen2024dual,
-      title={Dual-granularity Text-Guidance for Text-to-Image Generation}, 
-      author={Mitsui Chen and Yiyang Ma and Zesu Liu and Hong-Yu Zhou and Yu-cheng Chen and Jian-wei Liu and Shu-ui Liu and Yu-gang Jiang and Wei-shi Zheng},
-      year={2024},
-      eprint={2406.16510},
-      archivePrefix={arXiv},
-      primaryClass={cs.CV}
-}
-```
+---
+license: mit
+tags:
+- clip
+- feature-extraction
+---
+
+# DGTRS-CLIP-ViT-L-14
+
+This is the DGTRS-CLIP-ViT-L-14 model. It can be used for a variety of tasks, including zero-shot image classification and text-image retrieval.
+
+This model is compatible with both the `transformers` and `diffusers` libraries.
+
+## How to use
+
+### With `transformers`
+
+```python
+from transformers import CLIPProcessor, CLIPModel
+
+model = CLIPModel.from_pretrained("BiliSakura/DGTRS-CLIP-ViT-L-14")
+processor = CLIPProcessor.from_pretrained("BiliSakura/DGTRS-CLIP-ViT-L-14")
+
+# Your code here to use the model for image-text similarity, zero-shot classification, etc.
+```
+
+### With `diffusers`
+
+This model's text encoder can be used with Stable Diffusion:
+
+```python
+# Your code here to use the text encoder with a diffusion model.
+```
+
+## Citation
+
+If you use this model in your research, please cite the original paper:
+
+```
+@article{chen2025lrsclip,
+  title={LRSCLIP: A Vision-Language Foundation Model for Aligning Remote Sensing Image with Longer Text},
+  author={Chen, Weizhi and Chen, Jingbo and Deng, Yupeng and Chen, Jiansheng and Feng, Yuman and Xi, Zhihao and Liu, Diyou and Li, Kai and Meng, Yu},
+  journal={arXiv preprint arXiv:2503.19311},
+  year={2025}
+}
+```