From 79853f91152cbe1439cf4e7ceb82231b48ba8ae4 Mon Sep 17 00:00:00 2001 From: Letian88 <91178477+Letian88@users.noreply.github.com> Date: Thu, 4 Jul 2024 13:26:09 +0800 Subject: [PATCH] replace github address (#246) Co-authored-by: dp --- README.md | 4 ++-- unimol/README.md | 18 +++++++++--------- .../notebooks/unimol_binding_pose_demo.ipynb | 12 ++++++------ unimol/notebooks/unimol_pocket_repr_demo.ipynb | 4 ++-- unimol/requirements.txt | 2 +- unimol/setup.py | 2 +- unimol_docking_v2/README.md | 6 +++--- unimol_plus/README.md | 12 ++++++------ unimol_plus/setup.py | 2 +- unimol_tools/README.md | 2 +- unimol_tools/setup.py | 2 +- 11 files changed, 33 insertions(+), 33 deletions(-) diff --git a/README.md b/README.md index f655b0a..9839299 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ Shortcuts Uni-Mol: A Universal 3D Molecular Representation Learning Framework ------------------------------------------------------------------- -[[Paper](https://openreview.net/forum?id=6K2RM6wVqKu)], [[Uni-Mol Docking Colab](https://colab.research.google.com/github/dptech-corp/Uni-Mol/blob/main/unimol/notebooks/unimol_binding_pose_demo.ipynb)] +[[Paper](https://openreview.net/forum?id=6K2RM6wVqKu)], [[Uni-Mol Docking Colab](https://colab.research.google.com/github/deepmodeling/Uni-Mol/blob/main/unimol/notebooks/unimol_binding_pose_demo.ipynb)] Authors: Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke @@ -147,4 +147,4 @@ Please kindly cite our papers if you use the data/code/model. License ------- -This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/dptech-corp/Uni-Mol/blob/main/LICENSE) for additional details. +This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/deepmodeling/Uni-Mol/blob/main/LICENSE) for additional details. diff --git a/unimol/README.md b/unimol/README.md index 8005a92..25ffeae 100644 --- a/unimol/README.md +++ b/unimol/README.md @@ -1,7 +1,7 @@ Uni-Mol: A Universal 3D Molecular Representation Learning Framework =================================================================== -[[Paper](https://openreview.net/forum?id=6K2RM6wVqKu)], [[Uni-Mol Docking Colab](https://colab.research.google.com/github/dptech-corp/Uni-Mol/blob/main/unimol/notebooks/unimol_binding_pose_demo.ipynb)] +[[Paper](https://openreview.net/forum?id=6K2RM6wVqKu)], [[Uni-Mol Docking Colab](https://colab.research.google.com/github/deepmodeling/Uni-Mol/blob/main/unimol/notebooks/unimol_binding_pose_demo.ipynb)] Authors: Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke @@ -63,8 +63,8 @@ Uni-Mol's pretrained model weights | Model | File Size |Update Date | Download Link | |--------------------------|------------| ------------|--------------------------------------------------------------| -| molecular pretrain | 181MB | Aug 17 2022 |https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/mol_pre_no_h_220816.pt | -| pocket pretrain | 181MB | Aug 17 2022 |https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/pocket_pre_220816.pt | +| molecular pretrain | 181MB | Aug 17 2022 |https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/mol_pre_no_h_220816.pt | +| pocket pretrain | 181MB | Aug 17 2022 |https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/pocket_pre_220816.pt | Uni-Mol's finetuned model weights @@ -72,14 +72,14 @@ Uni-Mol's finetuned model weights | Model | File Size| Update Date| Download Link | |-------------------------------------------------|---------| -----------|--------------------------------------------------------------------| -| molecular conformation generation (qm9) | 181MB | Sep 8 2022 |https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/qm9_220908.pt | -| molecular conformation generation (drugs) | 181MB | Sep 8 2022 |https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/drugs_220908.pt | -| Protein-ligand binding pose prediction | 415MB | Sep 8 2022 |https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/binding_pose_220908.pt | +| molecular conformation generation (qm9) | 181MB | Sep 8 2022 |https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/qm9_220908.pt | +| molecular conformation generation (drugs) | 181MB | Sep 8 2022 |https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/drugs_220908.pt | +| Protein-ligand binding pose prediction | 415MB | Sep 8 2022 |https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/binding_pose_220908.pt | Dependencies ------------ - - [Uni-Core](https://github.com/dptech-corp/Uni-Core), check its [Installation Documentation](https://github.com/dptech-corp/Uni-Core#installation). + - [Uni-Core](https://github.com/deepmodeling/Uni-Core), check its [Installation Documentation](https://github.com/deepmodeling/Uni-Core#installation). - rdkit==2022.9.3, install via `pip install rdkit-pypi==2022.9.3` To use GPUs within docker you need to [install nvidia-docker-2](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker) first. Use the following command to pull the docker image: @@ -268,7 +268,7 @@ For ClinTox, Tox21, ToxCast, SIDER, HIV, PCBA and MUV, we set `loss_func=multi_t For ESOL, FreeSolv and Lipo, we set `loss_func=finetune_mse`. For QM7, QM8 and QM9, we set `loss_func=finetune_smooth_mae`. -**NOTE**: Our first version of the molecular pretraining ran with **all hydrogen** pretrained model, and above hyper-parameters are also for **all hydrogen** pretrained model. You can download the [all hydrogen model parameter](https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/mol_pre_all_h_220816.pt) here, and use it with `only_polar=-1` to reproduce our results. The performance of pretraining model with **no hydrogen** is very close to the **all hydrogen** one in molecular property prediction. We will update the hyperparameters for the no hydrogen version later. +**NOTE**: Our first version of the molecular pretraining ran with **all hydrogen** pretrained model, and above hyper-parameters are also for **all hydrogen** pretrained model. You can download the [all hydrogen model parameter](https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/mol_pre_all_h_220816.pt) here, and use it with `only_polar=-1` to reproduce our results. The performance of pretraining model with **no hydrogen** is very close to the **all hydrogen** one in molecular property prediction. We will update the hyperparameters for the no hydrogen version later. **NOTE**: For reproduce, you can do the validation on test set while training, with `--valid-subset valid` changing to `--valid-subset valid,test`. The model selection is still based on the performance of the valid set. It is controlled by `--best-checkpoint-metric $metric`. @@ -537,4 +537,4 @@ Please kindly cite this paper if you use the data/code/model. License ------- -This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/dptech-corp/Uni-Mol/blob/main/LICENSE) for additional details. +This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/deepmodeling/Uni-Mol/blob/main/LICENSE) for additional details. diff --git a/unimol/notebooks/unimol_binding_pose_demo.ipynb b/unimol/notebooks/unimol_binding_pose_demo.ipynb index 7c0d332..e9afa73 100644 --- a/unimol/notebooks/unimol_binding_pose_demo.ipynb +++ b/unimol/notebooks/unimol_binding_pose_demo.ipynb @@ -8,14 +8,14 @@ "source": [ "# Uni-Mol Binding Pose Prediction Colab\n", "\n", - "This Colab notebook provides an online runnable version of [Uni-Mol](https://github.com/dptech-corp/Uni-Mol/) binding pose prediction (short for \"docking\" in the following) with custom settings.\n", + "This Colab notebook provides an online runnable version of [Uni-Mol](https://github.com/deepmodeling/Uni-Mol/) binding pose prediction (short for \"docking\" in the following) with custom settings.\n", "Uni-Mol docking is very fast in dozens of seconds. \n", "\n", "Please note that this Colab notebook is not a finished product and is provided as an early-access prototype. It is provided for theoretical modeling only and caution should be exercised in its use. \n", "\n", "**Licenses**\n", "\n", - "This Colab uses the [Uni-Mol model parameters](https://github.com/dptech-corp/Uni-Mol/LICENSE) and its outputs are under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license. You can find details at: https://creativecommons.org/licenses/by/4.0/legalcode. The Colab is provided under the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0).\n", + "This Colab uses the [Uni-Mol model parameters](https://github.com/deepmodeling/Uni-Mol/LICENSE) and its outputs are under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license. You can find details at: https://creativecommons.org/licenses/by/4.0/legalcode. The Colab is provided under the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0).\n", "\n", "\n", "**Citations**\n", @@ -38,10 +38,10 @@ "%%bash\n", "#@title Install dependencies\n", "\n", - "GIT_REPO='https://github.com/dptech-corp/Uni-Mol'\n", - "UNICORE_URL='https://github.com/dptech-corp/Uni-Core/releases/download/0.0.2/unicore-0.0.1+cu116torch1.13.1-cp39-cp39-linux_x86_64.whl'\n", - "DOCKING_DATA_URL='https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/CASF-2016.tar.gz'\n", - "DOCKING_WEIGHT_URL='https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/binding_pose_220908.pt'\n", + "GIT_REPO='https://github.com/deepmodeling/Uni-Mol'\n", + "UNICORE_URL='https://github.com/deepmodeling/Uni-Core/releases/download/0.0.2/unicore-0.0.1+cu116torch1.13.1-cp39-cp39-linux_x86_64.whl'\n", + "DOCKING_DATA_URL='https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/CASF-2016.tar.gz'\n", + "DOCKING_WEIGHT_URL='https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/binding_pose_220908.pt'\n", "if [ ! -f UNIMOL_READY ]; then\n", " wget -q ${UNICORE_URL} \n", " pip3 -q install \"unicore-0.0.1+cu116torch1.13.1-cp39-cp39-linux_x86_64.whl\" \n", diff --git a/unimol/notebooks/unimol_pocket_repr_demo.ipynb b/unimol/notebooks/unimol_pocket_repr_demo.ipynb index 0c4f59d..46acfd8 100644 --- a/unimol/notebooks/unimol_pocket_repr_demo.ipynb +++ b/unimol/notebooks/unimol_pocket_repr_demo.ipynb @@ -40,8 +40,8 @@ "outputs": [], "source": [ "%%bash\n", - "pocket_data_url='https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/CASF-2016.tar.gz'\n", - "pocket_weight_url='https://github.com/dptech-corp/Uni-Mol/releases/download/v0.1/pocket_pre_220816.pt'\n", + "pocket_data_url='https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/CASF-2016.tar.gz'\n", + "pocket_weight_url='https://github.com/deepmodeling/Uni-Mol/releases/download/v0.1/pocket_pre_220816.pt'\n", "wget -q ${pocket_data_url}\n", "tar -xzf \"CASF-2016.tar.gz\"\n", "wget -q ${pocket_weight_url}" diff --git a/unimol/requirements.txt b/unimol/requirements.txt index 17c2162..e9a6f8a 100644 --- a/unimol/requirements.txt +++ b/unimol/requirements.txt @@ -1 +1 @@ -git+git://github.com/dptech-crop/Uni-Core.git@stable#egg=Uni-Core +git+git://github.com/deepmodeling/Uni-Core.git@stable#egg=Uni-Core diff --git a/unimol/setup.py b/unimol/setup.py index 07d09ac..11e12d5 100644 --- a/unimol/setup.py +++ b/unimol/setup.py @@ -10,7 +10,7 @@ author="DP Technology", author_email="unimol@dp.tech", license="The MIT License", - url="https://github.com/dptech-corp/Uni-Mol", + url="https://github.com/deepmodeling/Uni-Mol", packages=find_packages( exclude=["scripts", "tests", "example_data", "docker", "figure"] ), diff --git a/unimol_docking_v2/README.md b/unimol_docking_v2/README.md index 894be3e..c704a0a 100644 --- a/unimol_docking_v2/README.md +++ b/unimol_docking_v2/README.md @@ -12,7 +12,7 @@ Service of Uni-Mol Docking V2 is avaiable at https://bohrium.dp.tech/apps/unimol Dependencies ------------ - - [Uni-Core](https://github.com/dptech-corp/Uni-Core), check its [Installation Documentation](https://github.com/dptech-corp/Uni-Core#installation). + - [Uni-Core](https://github.com/deepmodeling/Uni-Core), check its [Installation Documentation](https://github.com/deepmodeling/Uni-Core#installation). - rdkit==2022.9.3, install via `pip install rdkit-pypi==2022.9.3 -i https://pypi.tuna.tsinghua.edu.cn/simple/ --trusted-host pypi.tuna.tsinghua.edu.cn` - biopandas==0.4.1, install via `pip install biopandas` @@ -21,7 +21,7 @@ Data | Data | File Size | Update Date | Download Link | |--------------------------|------------| ----------- |---------------------------------------------------------------------------------------------------------------------------| | Raw training data | 4.95GB | May 14 2024 |https://zenodo.org/records/11191555 | -| Posebusters and Astex | 8.2MB | Nov 16 2023 |https://github.com/dptech-corp/Uni-Mol/files/13352676/eval_sets.zip | +| Posebusters and Astex | 8.2MB | Nov 16 2023 |https://github.com/deepmodeling/Uni-Mol/files/13352676/eval_sets.zip | Note that we use the `Posebusters V1` (428 datapoints, released in August 2023). For the latest version, please refer to [Posebusters repo](https://github.com/maabuu/posebusters). @@ -113,4 +113,4 @@ Please kindly cite this paper if you use the data/code/model. License ------- -This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/dptech-corp/Uni-Mol/blob/main/LICENSE) for additional details. \ No newline at end of file +This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/deepmodeling/Uni-Mol/blob/main/LICENSE) for additional details. \ No newline at end of file diff --git a/unimol_plus/README.md b/unimol_plus/README.md index 348ecf2..f94f444 100644 --- a/unimol_plus/README.md +++ b/unimol_plus/README.md @@ -12,21 +12,21 @@ In the [PCQM4MV2](https://ogb.stanford.edu/docs/lsc/leaderboards/#pcqm4mv2) benc | Model Settings | # Layers | # Param. | Validation MAE | Model Checkpoint | |------------------|------------| ----------- |------------------|------------------| -| Uni-Mol+ | 12 | 52.4 M | 0.0696 | [link](https://github.com/dptech-corp/Uni-Mol/releases/download/v0.2/unimol_plus_pcq_base.pt) | -| Uni-Mol+ Large | 18 | 77 M | 0.0693 | [link](https://github.com/dptech-corp/Uni-Mol/releases/download/v0.2/unimol_plus_pcq_large.pt) | -| Uni-Mol+ Small | 6 | 27.7 M | 0.0714 | [link](https://github.com/dptech-corp/Uni-Mol/releases/download/v0.2/unimol_plus_pcq_small.pt) | +| Uni-Mol+ | 12 | 52.4 M | 0.0696 | [link](https://github.com/deepmodeling/Uni-Mol/releases/download/v0.2/unimol_plus_pcq_base.pt) | +| Uni-Mol+ Large | 18 | 77 M | 0.0693 | [link](https://github.com/deepmodeling/Uni-Mol/releases/download/v0.2/unimol_plus_pcq_large.pt) | +| Uni-Mol+ Small | 6 | 27.7 M | 0.0714 | [link](https://github.com/deepmodeling/Uni-Mol/releases/download/v0.2/unimol_plus_pcq_small.pt) | In the [OC20](https://opencatalystproject.org/leaderboard.html) IS2RE benchmark, Uni-Mol+ outperforms previous SOTA methods by a large margin. | Model Settings | # Layers | # Param. | Validation Mean MAE | Test Mean MAE | Model Checkpoint | |------------------|------------| ----------- |----------------------|----------------|------------------| -| Uni-Mol+ | 12 | 48.6 M | 0.4088 | 0.4143 | [link](https://github.com/dptech-corp/Uni-Mol/releases/download/v0.2/unimol_plus_oc20_base.pt) | +| Uni-Mol+ | 12 | 48.6 M | 0.4088 | 0.4143 | [link](https://github.com/deepmodeling/Uni-Mol/releases/download/v0.2/unimol_plus_oc20_base.pt) | Dependencies ------------ - - [Uni-Core](https://github.com/dptech-corp/Uni-Core) with pytorch > 2.0.0, check its [Installation Documentation](https://github.com/dptech-corp/Uni-Core#installation). + - [Uni-Core](https://github.com/deepmodeling/Uni-Core) with pytorch > 2.0.0, check its [Installation Documentation](https://github.com/deepmodeling/Uni-Core#installation). - rdkit==2022.09.3, install via `pip install rdkit==2022.09.3` - numba and pandas, install via `pip install numba pandas` @@ -128,4 +128,4 @@ Please kindly cite this paper if you use the data/code/model. License ------- -This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/dptech-corp/Uni-Mol/blob/main/LICENSE) for additional details. +This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/deepmodeling/Uni-Mol/blob/main/LICENSE) for additional details. diff --git a/unimol_plus/setup.py b/unimol_plus/setup.py index fd4f114..e455cfd 100644 --- a/unimol_plus/setup.py +++ b/unimol_plus/setup.py @@ -10,7 +10,7 @@ author="DP Technology", author_email="unimol@dp.tech", license="The MIT License", - url="https://github.com/dptech-corp/Uni-Mol", + url="https://github.com/deepmodeling/Uni-Mol", packages=find_packages( exclude=["scripts", "tests", "example_data", "docker", "figure"] ), diff --git a/unimol_tools/README.md b/unimol_tools/README.md index 01af610..0dc3405 100644 --- a/unimol_tools/README.md +++ b/unimol_tools/README.md @@ -31,7 +31,7 @@ pip install huggingface_hub pip install -r requirements.txt ## Clone repository -git clone https://github.com/dptech-corp/Uni-Mol.git +git clone https://github.com/deepmodeling/Uni-Mol.git cd Uni-Mol/unimol_tools ## Install diff --git a/unimol_tools/setup.py b/unimol_tools/setup.py index 1610eba..6d80b95 100644 --- a/unimol_tools/setup.py +++ b/unimol_tools/setup.py @@ -10,7 +10,7 @@ author="DP Technology", author_email="unimol@dp.tech", license="The MIT License", - url="https://github.com/dptech-corp/Uni-Mol/unimol_tools", + url="https://github.com/deepmodeling/Uni-Mol/unimol_tools", packages=find_packages( where='.', exclude=[