Instructions to use kerasformers/sam3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/sam3 with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use kerasformers/sam3 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kerasformers/sam3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5918f6ff3d24f5a98773387260d8925246fc8ad50418d6ccc98a64a791d9d5fd
- Size of remote file:
- 3.36 GB
- SHA256:
- a0bcbf75f8dd23444a3e72a7d8128aa66dc573e5f369c32053aecc5fd47775d5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.