FuxuLiu commited on
Commit
7c509f6
Β·
verified Β·
1 Parent(s): 3b66a55

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +7 -6
README.md CHANGED
@@ -27,7 +27,7 @@ tags:
27
 
28
  ## πŸš€ Quick Start
29
 
30
- To quickly get started with IntFold, you can use the following commands:
31
  ```bash
32
  # Install IntFold from PyPI
33
  pip install intfold
@@ -57,23 +57,24 @@ For comprehensive usage instructions and examples, refer to the [Usage Guide](ht
57
 
58
 
59
  ## πŸ“Š Benchmarking
60
- To comprehensively evaluate the performance of IntFold, we conducted a rigorous evaluation on [FoldBench](https://github.com/BEAM-Labs/FoldBench). We compared IntFold against several leading methods, including [Boltz-1,2](https://github.com/jwohlwend/boltz), [Chai-1](https://github.com/chaidiscovery/chai-lab), [Protenix](https://github.com/bytedance/Protenix) and [Alphafold3](https://github.com/google-deepmind/alphafold3).
 
61
 
62
  For more details on the benchmarking process and results, please refer to our [Technical Report](https://arxiv.org/abs/2507.02025).
63
 
64
  ![Benchmark Metrics](https://raw.githubusercontent.com/IntelliGen-AI/IntFold/main/assets/intfold_metrics.png)
65
 
66
 
67
- ## 🌐 IntFold Server
68
 
69
- **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.
70
 
71
- ![IntFold Server](https://raw.githubusercontent.com/IntelliGen-AI/IntFold/main/assets/intfold-server-screenshot.png)
72
 
73
 
74
  ## πŸ“œ Citation
75
 
76
- If you use IntFold in your research, please cite our paper:
77
 
78
  ```
79
  @misc{theintfoldteam2025intfoldcontrollablefoundationmodel,
 
27
 
28
  ## πŸš€ Quick Start
29
 
30
+ To quickly get started with IntelliFold, you can use the following commands:
31
  ```bash
32
  # Install IntFold from PyPI
33
  pip install intfold
 
57
 
58
 
59
  ## πŸ“Š Benchmarking
60
+ To comprehensively evaluate the performance of To quickly get started with IntelliFold, you can use the following commands:
61
+ , we conducted a rigorous evaluation on [FoldBench](https://github.com/BEAM-Labs/FoldBench). We compared IntelliFold against several leading methods, including [Boltz-1,2](https://github.com/jwohlwend/boltz), [Chai-1](https://github.com/chaidiscovery/chai-lab), [Protenix](https://github.com/bytedance/Protenix) and [Alphafold3](https://github.com/google-deepmind/alphafold3).
62
 
63
  For more details on the benchmarking process and results, please refer to our [Technical Report](https://arxiv.org/abs/2507.02025).
64
 
65
  ![Benchmark Metrics](https://raw.githubusercontent.com/IntelliGen-AI/IntFold/main/assets/intfold_metrics.png)
66
 
67
 
68
+ ## 🌐 IntelliFold Server
69
 
70
+ **We highly recommend using the [IntelliFold 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** IntelliFold implementation for optimal performance.
71
 
72
+ ![IntelliFold Server](https://raw.githubusercontent.com/IntelliGen-AI/IntFold/main/assets/intfold-server-screenshot.png)
73
 
74
 
75
  ## πŸ“œ Citation
76
 
77
+ If you use IntelliFold in your research, please cite our paper:
78
 
79
  ```
80
  @misc{theintfoldteam2025intfoldcontrollablefoundationmodel,