Instructions to use Dimsralf/srcnn-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Dimsralf/srcnn-model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Dimsralf/srcnn-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e18d2ca4d7442f2fb95c9e8b0f9a37ab213dc88d5dff3bf8bbe3e55ff159b54f
- Size of remote file:
- 464 kB
- SHA256:
- 4d5a57896a38fda5e0a8f9242befca1190249019cda736272dedead3fbc58717
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.