Instructions to use cafbr/minigpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use cafbr/minigpt with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://cafbr/minigpt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81b8fb282f0502b0bf47be144701c7e0b078e4835f8baff853d08438fcc67ab8
- Size of remote file:
- 398 kB
- SHA256:
- 909d866f49a3c01f35ed5179dc426fa8886b83ec1b428ae24bfc95f0b195738e
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