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wenda8759/AbFlow
AbFlow is a graph machine learning model from wenda8759. Use it for the graph machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-4.0.
All datasets and pre-trained model weights are available on Hugging Face:
Downloads · 30 days
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Updated Dec 29, 2025
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1.9 GB
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From the Hugging Face model README
All datasets and pre-trained model weights are available on Hugging Face:
🤗 https://huggingface.co/wenda8759/AbFlow
# Install huggingface_hub if not already installed
pip install huggingface_hub
# Download all files
huggingface-cli download wenda8759/AbFlow --local-dir ./
# Or download specific files
huggingface-cli download wenda8759/AbFlow checkpoints/multi_cdr_design.ckpt --local-dir ./
from huggingface_hub import snapshot_download, hf_hub_download
# Download entire repository
snapshot_download(repo_id="wenda8759/AbFlow", local_dir="./")
# Or download specific file
hf_hub_download(
repo_id="wenda8759/AbFlow",
filename="checkpoints/multi_cdr_design.ckpt",
local_dir="./"
)
| Model | Description | File |
|---|---|---|
| Paratope-Centric Design | Design based on epitope | checkpoints/paratope_centric_design.ckpt |
| Multi-CDR Design | Design all 6 CDR regions | checkpoints/multi_cdr_design.ckpt |
| Structure Prediction | Predict antibody structure | checkpoints/structure_prediction.ckpt |
| Affinity Optimization | Optimize binding affinity | checkpoints/affinity_optimization.ckpt |
| ΔΔG Predictor | Predict binding energy changes | checkpoints/ddg_predictor.ckpt |
After downloading, organize your data as follows:
AbFlow/
├── datasets/
│ ├── RAbD/
│ │ ├── train.json
│ │ ├── valid.json
│ │ ├── test.json
│ │ ├── train.pkl
│ │ ├── valid.pkl
│ │ ├── test.pkl
│ │ ├── train_surf.pkl
│ │ ├── valid_surf.pkl
│ │ └── test_surf.pkl
│ └── IgFold/
│ ├── train.json
│ ├── valid.json
│ ├── test.json
│ └── ...
└── checkpoints/
├── multi_cdr_design.ckpt
├── structure_prediction.ckpt
└── ...