Instructions to use dltest12345/testmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use dltest12345/testmodel 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://dltest12345/testmodel") - Notebooks
- Google Colab
- Kaggle
Download simple_mal_model4.pt from dltest12345/testmodel: direct link, hf CLI and curl.
- Browser
- Download file 1.32 kB
-
https://huggingface.co/dltest12345/testmodel/resolve/main/simple_mal_model4.pt
- Command line
-
hf download hf://dltest12345/testmodel/simple_mal_model4.pt
-
curl -L -o simple_mal_model4.pt https://huggingface.co/dltest12345/testmodel/resolve/main/simple_mal_model4.pt
1.32 kB
- Xet hash:
- da1c444001c0e4e8fc2e20b58e4a0a5513f7676bb85ee64cb8ce57c2466bd56d
- Size of remote file:
- 1.32 kB
- SHA256:
- 96fa7bb7dbd27afc9cb8946da192fb48db07d2429e062f2073a385a8708529dc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.