Instructions to use LeninKh/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use LeninKh/test with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://LeninKh/test") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
datasets:
- dpdl-benchmark/plant_village
language:
- en
metrics:
- accuracy
widget:
- src: >-
https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: >-
https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
pipeline_tag: image-classification
library_name: keras
tags:
- medical