Update README.md

README.md

@@ -1,3 +1,54 @@
 ---
 license: apache-2.0
+datasets:
+- AlexFierro9/Kinetics400
+- imagenet-1k
+- HuggingFaceM4/something_something_v2
+language:
+- en
+pipeline_tag: video-classification
 ---
+
+
+
+<br>
+
+# VideoMamba
+
+## Model Details
+
+VideoMamba is a purely SSM-based model for video understanding.
+
+- **Developed by:** [OpenGVLab](https://github.com/OpenGVLab)
+- **Model type:** An efficient backbone based on the bidirectional state space model.
+- **License:** Non-commercial license
+
+
+### Model Sources
+
+- **Repository:** https://github.com/OpenGVLab/VideoMamba
+- **Paper:** https://arxiv.org/abs/2403.06977
+
+## Uses
+
+The primary use of VideoMamba is research on image and video tasks, e.g., image classification, action recognition, long-term video understanding, and video-text retrieval, with an SSM-based backbone.
+The primary intended users of the model are researchers and hobbyists in computer vision, machine learning, and artificial intelligence.
+
+## How to Get Started with the Model
+
+- You can replace the backbone for video tasks with the proposed VideoMamba: https://github.com/OpenGVLab/VideoMamba/blob/main/videomamba/video_sm/models/videomamba.py
+- Then you can load this checkpoint and start training.
+
+
+### Citation Information
+
+```
+@misc{li2024videomamba,
+      title={VideoMamba: State Space Model for Efficient Video Understanding}, 
+      author={Kunchang Li and Xinhao Li and Yi Wang and Yinan He and Yali Wang and Limin Wang and Yu Qiao},
+      year={2024},
+      eprint={2403.06977},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```