Instructions to use Arabic-Clip/Arabert-v2-base-ViT-B-16-SigLIP-512-2M-mscoco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Arabic-Clip/Arabert-v2-base-ViT-B-16-SigLIP-512-2M-mscoco with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Arabic-Clip/Arabert-v2-base-ViT-B-16-SigLIP-512-2M-mscoco") - Notebooks
- Google Colab
- Kaggle
Arabert-v2-base-ViT-B-16-SigLIP-512-2M-mscoco / Arabert-v2-base-ViT-B-16-SigLIP-512-2M-mscoco.pickle
- Xet hash:
- 7d0a2781a277e9a9aa085fe4079617acd6575930c750c2680b43c212badd3534
- Size of remote file:
- 2.36 MB
- SHA256:
- 78c10ff89b117694d0bc80999e622c11b8c1bb5604c109066d4ef7dc19b0f021
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