Instructions to use merve/text_image_dual_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use merve/text_image_dual_encoder 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://merve/text_image_dual_encoder") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from merve/text_image_dual_encoder: direct link, hf CLI and curl.
- Browser
- Download file 10.9 MB
-
https://huggingface.co/merve/text_image_dual_encoder/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://merve/text_image_dual_encoder@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/merve/text_image_dual_encoder/resolve/refs%2Fpr%2F1/saved_model.pb
10.9 MB
- Xet hash:
- 9f3e69b73c8a19aec50693f17a1bb32c9cec274eb1709ad425626fc12bbd25b0
- Size of remote file:
- 10.9 MB
- SHA256:
- 45cee569b2c02ccb5674f26afe218a6b750bb32c81846a6e94e6bab18af16695
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