Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: mit
+library_name: transformers
+pipeline_tag: image-text-to-text
+---
+![header](./assets/assets_header.png) 
+
+<p align="center">
+   📃 <a href="https://arxiv.org/abs/2409.02889" target="_blank">Paper</a> • 🌐 <a href="" target="_blank">Demo</a> • 📃 <a href="https://github.com/FreedomIntelligence/LongLLaVA" target="_blank">Github</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/LongLLaVA-53B-A13B" target="_blank">LongLLaVA-53B-A13B</a>
+</p>
+
+![efficiency](./assets/singleGPU.png) 
+
+
+## 🌈 Update
+
+* **[2024.09.05]** LongLLaVA repo is published！🎉 The Code will
+
+## Architecture
+
+<details>
+  <summary>Click to view the architecture image</summary>
+
+  ![Architecture Image](./assets/arch.png)
+
+</details>
+
+
+## Results
+
+<details>
+  <summary>Click to view the Results</summary>
+
+  - Main Results
+      ![Main Results](./assets/result1.png) 
+  - Diagnostic Results
+      ![Diagnostic Results](./assets/diaresult.png)
+  - Video-NIAH
+      ![Video-NIAH](./assets/NIAH.png)
+
+</details>
+
+
+
+## Results reproduction
+
+
+### Evaluation
+
+- Preparation
+
+Get the model inference code from [Github](https://github.com/FreedomIntelligence/LongLLaVA).
+
+```bash
+git clone https://github.com/FreedomIntelligence/LongLLaVA.git
+```
+
+- Environment Setup
+
+```bash
+pip install -r requirements.txt
+```
+
+
+- Command Line Interface
+
+```bash
+python cli.py --model_dir path-to-longllava
+```
+
+
+- Model Inference
+
+```python
+query = 'What does the picture show?'
+image_paths = ['image_path1'] # image or video path
+
+from cli import Chatbot
+bot = Chatbot(path-to-longllava)
+output = bot.chat(query, image_paths)
+print(output) # Prints the output of the model
+```
+
+
+## Acknowledgement
+
+- [LLaVA](https://github.com/haotian-liu/LLaVA): Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
+
+## Citation
+
+```
+@misc{wang2024longllavascalingmultimodalllms,
+      title={LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via Hybrid Architecture}, 
+      author={Xidong Wang and Dingjie Song and Shunian Chen and Chen Zhang and Benyou Wang},
+      year={2024},
+      eprint={2409.02889},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2409.02889}, 
+}
+```
+
+
+