Instructions to use dvdface/next-frame-predict with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use dvdface/next-frame-predict with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("dvdface/next-frame-predict") - Notebooks
- Google Colab
- Kaggle
Download configuration.py from dvdface/next-frame-predict: direct link, hf CLI and curl.
- Browser
- Download file 300 Bytes
-
https://huggingface.co/dvdface/next-frame-predict/resolve/main/configuration.py
- Command line
-
hf download hf://dvdface/next-frame-predict/configuration.py
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curl -L -o configuration.py https://huggingface.co/dvdface/next-frame-predict/resolve/main/configuration.py
300 Bytes
| from transformers import PretrainedConfig | |
| class PredNetConfig(PretrainedConfig): | |
| model_type = "prednet" | |
| def __init__(self, sequence_len=4, resize_hw=(128, 128), **kwargs): | |
| super().__init__(**kwargs) | |
| self.sequence_len = sequence_len | |
| self.resize_hw = list(resize_hw) | |