Instructions to use HBDX/Seq-TransfoRNA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HBDX/Seq-TransfoRNA with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HBDX/Seq-TransfoRNA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download setup.py from HBDX/Seq-TransfoRNA: direct link, hf CLI and curl.
- Browser
- Download file 1.29 kB
-
https://huggingface.co/HBDX/Seq-TransfoRNA/resolve/main/setup.py
- Command line
-
hf download hf://HBDX/Seq-TransfoRNA/setup.py
-
curl -L -o setup.py https://huggingface.co/HBDX/Seq-TransfoRNA/resolve/main/setup.py
1.29 kB
| from setuptools import find_packages, setup | |
| setup( | |
| name='TransfoRNA', | |
| version='0.0.1', | |
| description='TransfoRNA: Navigating the Uncertainties of Small RNA Annotation with an Adaptive Machine Learning Strategy', | |
| url='https://github.com/gitHBDX/TransfoRNA', | |
| author='YasserTaha,JuliaJehn', | |
| author_email='ytaha@hb-dx.com,jjehn@hb-dx.com,tsikosek@hb-dx.com', | |
| classifiers=[ | |
| 'Development Status :: 4 - Beta', | |
| 'Intended Audience :: Biological Researchers', | |
| 'License :: OSI Approved :: MIT License', | |
| 'Programming Language :: Python :: 3.9', | |
| ], | |
| packages=find_packages(include=['transforna', 'transforna.*']), | |
| install_requires=[ | |
| "anndata==0.8.0", | |
| "dill==0.3.6", | |
| "hydra-core==1.3.0", | |
| "imbalanced-learn==0.9.1", | |
| "matplotlib==3.5.3", | |
| "numpy==1.22.3", | |
| "omegaconf==2.2.2", | |
| "pandas==1.5.2", | |
| "plotly==5.10.0", | |
| "PyYAML==6.0", | |
| "rich==12.6.0", | |
| "viennarna>=2.5.0a5", | |
| "scanpy==1.9.1", | |
| "scikit_learn==1.2.0", | |
| "skorch==0.12.1", | |
| "torch==1.10.1", | |
| "tensorboard==2.16.2", | |
| "Levenshtein==0.21.0" | |
| ], | |
| python_requires='>=3.9', | |
| #move yaml files to package | |
| package_data={'': ['*.yaml']}, | |
| ) | |