Instructions to use simiaoAA/cross-species-aging-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use simiaoAA/cross-species-aging-models with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://simiaoAA/cross-species-aging-models") - Notebooks
- Google Colab
- Kaggle
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Download README.md from simiaoAA/cross-species-aging-models: direct link, hf CLI and curl.
- Browser
- Download file 573 Bytes
-
https://huggingface.co/simiaoAA/cross-species-aging-models/resolve/main/README.md
- Command line
-
hf download hf://simiaoAA/cross-species-aging-models/README.md
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curl -L -o README.md https://huggingface.co/simiaoAA/cross-species-aging-models/resolve/main/README.md
573 Bytes
metadata
license: mit
library_name: keras
tags:
- keras
- tensorflow
- single-cell
- aging
- domain-adaptation
- cross-species
pretty_name: Cross-species aging DANN models
Cross-Species Aging DANN Models
This model repository stores trained Keras/TensorFlow model files required by the GitHub reproducibility package:
https://github.com/SimiaoZhao/cross-species-aging-resource
Inputs must be aligned to the feature lists distributed with the dataset repository. During peer review, access may be restricted to reviewers and editors.