Instructions to use mfidabel/instruct-pix2pix-tensorflow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use mfidabel/instruct-pix2pix-tensorflow 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://mfidabel/instruct-pix2pix-tensorflow") - Notebooks
- Google Colab
- Kaggle
Download diffusion_model.h5 from mfidabel/instruct-pix2pix-tensorflow: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/mfidabel/instruct-pix2pix-tensorflow/resolve/main/diffusion_model.h5
- Command line
-
hf download hf://mfidabel/instruct-pix2pix-tensorflow/diffusion_model.h5
-
curl -L -o diffusion_model.h5 https://huggingface.co/mfidabel/instruct-pix2pix-tensorflow/resolve/main/diffusion_model.h5
3.44 GB
- Xet hash:
- 1ce2203a0c2d22c0543a95258dafa2196b24880ac83ea51b05df2f5dd7942791
- Size of remote file:
- 3.44 GB
- SHA256:
- bb0d3cd1bbc8b15642a59d3e23127f7511f3638c1db830e807f734a4d4429997
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