Time Series Forecasting
Keras
English
deeplearning
ConvoLSTM
Cloudcover-prediction
Satellite
data
dataanalysis
timeseries
code
tensorflow
machinelearning
Instructions to use Hrishi-2003/Cloud-Cover-Nowcasting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Hrishi-2003/Cloud-Cover-Nowcasting 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://Hrishi-2003/Cloud-Cover-Nowcasting") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from Hrishi-2003/Cloud-Cover-Nowcasting: direct link, hf CLI and curl.
- Browser
- Download file 59 Bytes
-
https://huggingface.co/Hrishi-2003/Cloud-Cover-Nowcasting/resolve/main/__init__.py
- Command line
-
hf download hf://Hrishi-2003/Cloud-Cover-Nowcasting/__init__.py
-
curl -L -o __init__.py https://huggingface.co/Hrishi-2003/Cloud-Cover-Nowcasting/resolve/main/__init__.py
59 Bytes
| # This file marks the `src` directory as a Python package. | |