Instructions to use jsebdev/apple_stock_predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use jsebdev/apple_stock_predictor 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://jsebdev/apple_stock_predictor") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from jsebdev/apple_stock_predictor: direct link, hf CLI and curl.
- Browser
- Download file 2.15 MB
-
https://huggingface.co/jsebdev/apple_stock_predictor/resolve/main/saved_model.pb
- Command line
-
hf download hf://jsebdev/apple_stock_predictor/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/jsebdev/apple_stock_predictor/resolve/main/saved_model.pb
2.15 MB
- Xet hash:
- 147f47f36bb4dc80754eb8ca9453ef742665a4d96553250dfa984436ec392128
- Size of remote file:
- 2.15 MB
- SHA256:
- a5aac0f5c87abba491d06c63247e1e41290d3426bc7f4f9f30c8b0c7f94c9180
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