Instructions to use funlab/DeepLoop-CPGZ-LoopDenoise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use funlab/DeepLoop-CPGZ-LoopDenoise with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://funlab/DeepLoop-CPGZ-LoopDenoise") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c795f4b932783275c2cea9ce4d9209ef7272dc4c7c916eae59684501d34298cb
- Size of remote file:
- 23.3 kB
- SHA256:
- f6aeab77ba5dc52342785b66e9ca2740126306e54d875fef7d43cbb07966824d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.