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 text_encoder.h5 from mfidabel/instruct-pix2pix-tensorflow: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/mfidabel/instruct-pix2pix-tensorflow/resolve/main/text_encoder.h5
- Command line
-
hf download hf://mfidabel/instruct-pix2pix-tensorflow/text_encoder.h5
-
curl -L -o text_encoder.h5 https://huggingface.co/mfidabel/instruct-pix2pix-tensorflow/resolve/main/text_encoder.h5
492 MB
- Xet hash:
- 8d0373b63ad871c1b5ea8e4794a80d7df896adecae7fc143411530773d338343
- Size of remote file:
- 492 MB
- SHA256:
- 08c64755ed3fd73db096d1369be33db886710e334add31ac3335cf79a1466687
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