update doc for 0.1.0

Author: liugangcode

docs/source/conf.py

@@ -9,7 +9,7 @@
 project = 'torch-molecule'
 copyright = '2025, Gang Liu'
 author = 'Gang Liu'
-release = '0.1'
+release = '0.1.0'
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

docs/source/example.rst

@@ -3,7 +3,6 @@ Examples
 
 This section shows how to use the `torch_molecule` library in practice. More examples are available in the `examples <https://github.com/liugangcode/torch-molecule/tree/main/examples/>`_ folder and the `tests <https://github.com/liugangcode/torch-molecule/tree/main/tests/>`_ folder.
 
-
 Molecular Property Prediction Usage
 -----------------------------------
 

docs/source/index.rst

@@ -4,7 +4,7 @@
 torch-molecule documentation
 ============================
 
-Welcome to the torch-molecule. torch-molecule is an actively developed package designed to facilitate molecular discovery through deep learning. 
+Welcome to the torch-molecule. torch-molecule is a deep learning package designed for molecular discovery. 
 
 It offers a user-friendly interface similar to `sklearn`, and includes model checkpoints for efficient deployment and benchmarking across various molecular tasks. The package currently focuses on three main components:
 

docs/source/install.rst

@@ -4,13 +4,33 @@ Installation
 To install `torch-molecule`, follow these steps:
 
 1. **Create a Conda environment**:
+   ```bash
+   conda create --name torch_molecule python=3.11.7
+   conda activate torch_molecule
+   ```
 
-   .. code-block:: bash
+2. **Install using pip (0.1.0)**:
+
+   ```bash
+   pip install torch-molecule
+   ```
+
+3. **Install from source for the latest version**:
+
+   Clone the repository:
+
+   ```bash
+   git clone https://github.com/liugangcode/torch-molecule
+   cd torch-molecule
+   ```
 
-      conda create --name torch_molecule python=3.11.7
-      conda activate torch_molecule
+   Install:
 
-2. **Install `torch_molecule` from GitHub**:
+   ```bash
+   pip install .
+   ```
+
+4. **Install editable `torch_molecule` (for developer)**:
 
    Clone the repository:
 
@@ -30,37 +50,11 @@ To install `torch-molecule`, follow these steps:
 
       pip install -e .
 
-3. **Install `torch_molecule` from PyPI** (Legacy):
-   
-   .. code-block:: bash
-
-      pip install -i https://test.pypi.org/simple/ torch-molecule
-
-**Required Dependencies**:
-
-Dependencies are listed in `requirements.txt <https://github.com/liugangcode/torch-molecule/requirements.txt>`_. Example contents:
-
-.. code-block:: text
-
-   # Install PyTorch with CUDA 11.8
-   -f https://download.pytorch.org/whl/cu118/torch_stable.html
-   torch==2.2.0+cu118
-
-   # Install PyTorch Geometric and related packages
-   -f https://data.pyg.org/whl/torch-2.2.0+cu118.html
-   torch_geometric==2.6.1
-   torch_cluster
-   torch_scatter
 
-   # Other dependencies
-   huggingface_hub
-   joblib==1.3.2
-   networkx==3.2.1
-   pandas==2.2.3
-   PyYAML==6.0.2
-   rdkit==2023.9.5
-   scikit_learn==1.4.1.post1
-   scipy==1.14.1
-   tqdm==4.66.2
+### Additional Packages
 
-   optuna
+| Model | Required Packages |
+|-------|-------------------|
+| HFPretrainedMolecularEncoder | transformers |
+| BFGNNMolecularPredictor | torch-scatter |
+| GRINMolecularPredictor | torch-scatter |