Instructions to use logasja/instagram-maven with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/instagram-maven 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://logasja/instagram-maven") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from logasja/instagram-maven: direct link, hf CLI and curl.
- Browser
- Download file 137 MB
-
https://huggingface.co/logasja/instagram-maven/resolve/main/model.weights.h5
- Command line
-
hf download hf://logasja/instagram-maven/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/logasja/instagram-maven/resolve/main/model.weights.h5
137 MB
- Xet hash:
- 0f94db9e85cefead3e5979acecdadd451ffa15aa049971cfaa23c32aaca743eb
- Size of remote file:
- 137 MB
- SHA256:
- 8250980a41dddad0baec94a8d6921da06c2bc66e4641da9e40ab344de2607345
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.