Instructions to use snigdha05/DataSynthis_ML_JobTask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use snigdha05/DataSynthis_ML_JobTask 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://snigdha05/DataSynthis_ML_JobTask") - Notebooks
- Google Colab
- Kaggle
Download arima_model.pkl from snigdha05/DataSynthis_ML_JobTask: direct link, hf CLI and curl.
- Browser
- Download file 2.86 MB
-
https://huggingface.co/snigdha05/DataSynthis_ML_JobTask/resolve/main/arima_model.pkl
- Command line
-
hf download hf://snigdha05/DataSynthis_ML_JobTask/arima_model.pkl
-
curl -L -o arima_model.pkl https://huggingface.co/snigdha05/DataSynthis_ML_JobTask/resolve/main/arima_model.pkl
2.86 MB
- Xet hash:
- 8130f005ddf665ad3de695b5096eea8712d444763ecbf18f3d883535069270e1
- Size of remote file:
- 2.86 MB
- SHA256:
- 85cf2d91c5b7683795ec709dc31b160d59af4cc08abdb1df443c8ff2875748b1
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