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
Download train_embrna_model_multi0401.keras from simiaoAA/cross-species-aging-models: direct link, hf CLI and curl.
- Browser
- Download file 368 MB
-
https://huggingface.co/simiaoAA/cross-species-aging-models/resolve/main/train_embrna_model_multi0401.keras
- Command line
-
hf download hf://simiaoAA/cross-species-aging-models/train_embrna_model_multi0401.keras
-
curl -L -o train_embrna_model_multi0401.keras https://huggingface.co/simiaoAA/cross-species-aging-models/resolve/main/train_embrna_model_multi0401.keras
368 MB
- Xet hash:
- 32642a794460c4327a5947155a7f9849c2f7ae6c219537fd63ee2d434c20578a
- Size of remote file:
- 368 MB
- SHA256:
- d79c6248e8d28da0f8a5d5b49972ff3fbb701ef0e40734d1f28e6cc3f0bfe629
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