Instructions to use ashrafnsu/DataSynthis_Job_task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ashrafnsu/DataSynthis_Job_task 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://ashrafnsu/DataSynthis_Job_task") - Notebooks
- Google Colab
- Kaggle
Download svd_model.keras from ashrafnsu/DataSynthis_Job_task: direct link, hf CLI and curl.
- Browser
- Download file 5.94 MB
-
https://huggingface.co/ashrafnsu/DataSynthis_Job_task/resolve/main/svd_model.keras
- Command line
-
hf download hf://ashrafnsu/DataSynthis_Job_task/svd_model.keras
-
curl -L -o svd_model.keras https://huggingface.co/ashrafnsu/DataSynthis_Job_task/resolve/main/svd_model.keras
5.94 MB
- Xet hash:
- 48299599fd5d4443e39c92b007f4790e8af3294854e56d83db92b60d1a01b53c
- Size of remote file:
- 5.94 MB
- SHA256:
- 7d505b90ddc28359367876fd92d26a68ae027a62d91ebee7f4ff4e7a75f673ca
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