Upload README.md

README.md

@@ -7,7 +7,7 @@ tags:
 - biomolecular-structure-prediction
 ---
 
-![IntFold Cover](https://github.com/IntelliGen-AI/IntFold/assets/intfold-cover.png)
+![IntFold Cover](https://github.com/IntelliGen-AI/IntFold/blob/main/assets/intfold-cover.png)
 
 # IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction.
 [![HuggingFace Models](https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Models-yellow)](https://huggingface.co/GAGABIG/CNN)
@@ -22,7 +22,7 @@ tags:
 </div>
 
 
-![IntFold Model](https://github.com/IntelliGen-AI/IntFold/assets/Intfold-Model-Arc.png)
+![IntFold Model](https://github.com/IntelliGen-AI/IntFold/blob/main/assets/Intfold-Model-Arc.png)
 
 
 ## 🚀 Quick Start
@@ -37,23 +37,23 @@ intfold predict ./examples/5S8I_A.yaml --out_dir ./output
 
 ## ⚙️ Installation
 
-To more complete installation instructions and usage, please refer to the [Installation Guide](https://github.com/IntelliGen-AI/IntFold/docs/installation.md).
+To more complete installation instructions and usage, please refer to the [Installation Guide](https://github.com/IntelliGen-AI/IntFold/blob/main/docs/installation.md).
 
 
 ## 🔍 Inference
 
-1. **Prepare Input File**: Create a YAML file with your sequences following our [input format specification](https://github.com/IntelliGen-AI/IntFold/docs/input_yaml_format.md)
+1. **Prepare Input File**: Create a YAML file with your sequences following our [input format specification](https://github.com/IntelliGen-AI/IntFold/blob/main/docs/input_yaml_format.md)
 
 2. **Run Prediction**:
    ```bash
    intfold predict your_input.yaml --out_dir ./results
    ```
 
-3. **Check Results**: Find predicted structures and confidence scores in the output directory, you can also check the section of **output format** in [output documentation](https://github.com/IntelliGen-AI/IntFold/docs/input_yaml_format.md#output-format).
+3. **Check Results**: Find predicted structures and confidence scores in the output directory, you can also check the section of **output format** in [output documentation](https://github.com/IntelliGen-AI/IntFold/blob/main/docs/input_yaml_format.md#output-format).
 
-4. **Optional Optimization**: Enable [custom kernels](https://github.com/IntelliGen-AI/IntFold/docs/kernels.md) for faster inference and reduced memory usage
+4. **Optional Optimization**: Enable [custom kernels](https://github.com/IntelliGen-AI/IntFold/blob/main/docs/kernels.md) for faster inference and reduced memory usage
 
-For comprehensive usage instructions and examples, refer to the [Usage Guide](https://github.com/IntelliGen-AI/IntFold/docs/usage.md).
+For comprehensive usage instructions and examples, refer to the [Usage Guide](https://github.com/IntelliGen-AI/IntFold/blob/main/docs/usage.md).
 
 
 ## 📊 Benchmarking
@@ -61,14 +61,14 @@ To comprehensively evaluate the performance of IntFold, we conducted a rigorous
 
 For more details on the benchmarking process and results, please refer to our [Technical Report](https://intfold-server-dev.oss-cn-hongkong.aliyuncs.com/IntFold_Technical_Report.pdf).
 
-![Benchmark Metrics](https://github.com/IntelliGen-AI/IntFold/assets/intfold_metrics.png)
+![Benchmark Metrics](https://github.com/IntelliGen-AI/IntFold/blob/main/assets/intfold_metrics.png)
 
 
 ## 🌐 IntFold Server
 
 **We highly recommend using the [IntFold Server](https://server.intfold.com) for the most accurate, complete, and convenient biomolecular structure predictions.** It requires no installation and provides an intuitive web interface to submit your sequences and visualize results directly in your browser. The server runs the **full, optimized, latest** IntFold implementation for optimal performance.
 
-![IntFold Server](https://github.com/IntelliGen-AI/IntFold/assets/intfold-server-screenshot.png)
+![IntFold Server](https://github.com/IntelliGen-AI/IntFold/blob/main/assets/intfold-server-screenshot.png)
 
 
 ## 📜 Citation
@@ -88,7 +88,7 @@ the official citation will be available soon.
 
 ## ⚖️ License
 
-The IntFold project, including code and model parameters, is made available under the [Apache 2.0 License](https://github.com/IntelliGen-AI/IntFold/LICENSE), it is free for both academic research and commercial use.
+The IntFold project, including code and model parameters, is made available under the [Apache 2.0 License](https://github.com/IntelliGen-AI/IntFold/blob/main/LICENSE), it is free for both academic research and commercial use.
 
 ## 📬 Contact Us