Installation
Installation via pip
Using uv (Recommended)
uv is a modern, fast Python package and project manager. It’s significantly faster than traditional tools.
Install uv (if not already installed):
# On macOS and Linux curl -LsSf https://astral.sh/uv/install.sh | sh # On Windows powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
Create and activate a new environment (tested with Python >=3.10):
uv venv --python 3.10 sarcasm source sarcasm/bin/activate # On macOS/Linux # Or: sarcasm\Scripts\activate # On Windows
Install SarcAsM and its dependencies via uv:
uv pip install sarc-asm
Note
PyTorch will be installed automatically with CUDA support if available. For specific CUDA versions or CPU-only installation, see the PyTorch installation guide.
Using conda
Alternatively, you can use conda for environment management:
Create and activate a new environment (tested with Python >=3.10):
conda create -n sarcasm python==3.10 conda activate sarcasm
Install SarcAsM and its dependencies via pip from PyPI:
pip install sarc-asm
Note
PyTorch will be installed automatically with CUDA support if available. For specific CUDA versions or CPU-only installation, see the PyTorch installation guide.
Installation via GitHub
Using uv (Recommended)
Clone repo from git:
git clone https://github.com/danihae/SarcAsM cd SarcAsM
Create a new environment (tested with Python >=3.10):
uv venv --python 3.10 source .venv/bin/activate # On macOS/Linux # Or: .venv\Scripts\activate # On Windows
Install all the required packages via:
uv pip install .
Note
PyTorch will be installed automatically with CUDA support if available. For specific CUDA versions or CPU-only installation, see the PyTorch installation guide.
Using conda
Clone repo from git:
git clone https://github.com/danihae/SarcAsM cd SarcAsM
Create a new environment (tested with Python >=3.10):
conda create -n sarcasm python==3.10 conda activate sarcasm
Install all the required packages from pip via:
pip install .
Note
PyTorch will be installed automatically with CUDA support if available. For specific CUDA versions or CPU-only installation, see the PyTorch installation guide.
The full installation usually takes less than 2 min, depending on internet connection.