Instructions to use Umair2002/codeLevelGemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Umair2002/codeLevelGemma 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://Umair2002/codeLevelGemma") - Notebooks
- Google Colab
- Kaggle
Download codeLevelGemma.keras from Umair2002/codeLevelGemma: direct link, hf CLI and curl.
- Browser
- Download file 4.01 GB
-
https://huggingface.co/Umair2002/codeLevelGemma/resolve/main/codeLevelGemma.keras
- Command line
-
hf download hf://Umair2002/codeLevelGemma/codeLevelGemma.keras
-
curl -L -o codeLevelGemma.keras https://huggingface.co/Umair2002/codeLevelGemma/resolve/main/codeLevelGemma.keras
4.01 GB
- Xet hash:
- 6f5e044c0349071e31355edc6e885d2ddc0b4a0dfc041fe98cbcfb810245669d
- Size of remote file:
- 4.01 GB
- SHA256:
- 08a1e9f8edad39008565d24a52231735c2b7f318397a6143b7de4d32f28fc233
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