Instructions to use amgadhasan/arabic-image-captioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use amgadhasan/arabic-image-captioner 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("amgadhasan/arabic-image-captioner") - Notebooks
- Google Colab
- Kaggle
Download model/decoder/fingerprint.pb from amgadhasan/arabic-image-captioner: direct link, hf CLI and curl.
- Browser
- Download file 57 Bytes
-
https://huggingface.co/amgadhasan/arabic-image-captioner/resolve/main/model/decoder/fingerprint.pb
- Command line
-
hf download hf://amgadhasan/arabic-image-captioner/model/decoder/fingerprint.pb
-
curl -L -o fingerprint.pb https://huggingface.co/amgadhasan/arabic-image-captioner/resolve/main/model/decoder/fingerprint.pb
57 Bytes
- Xet hash:
- 340a6316e39f983b3e2ca1d4f756b48b28bb86d9352bd5afc519805417baaa6d
- Size of remote file:
- 57 Bytes
- SHA256:
- 92658694177f3b40a5224bf1c1831fdeba388860440803f7e397a54568d86487
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.