Image Classification
Keras
LiteRT
LiteRT
English
Portuguese
computer-vision
tensorflow
mobilenetv2
transfer-learning
on-device
android
mobile
accessibility
assistive-technology
visually-impaired
banknote-recognition
currency-recognition
brazilian-real
brazil
portuguese
Eval Results (legacy)
Instructions to use arthursilvadantas/NotavelAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use arthursilvadantas/NotavelAI 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://arthursilvadantas/NotavelAI") - LiteRT
How to use arthursilvadantas/NotavelAI with LiteRT:
# 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
- Notebooks
- Google Colab
- Kaggle
Download classes.json from arthursilvadantas/NotavelAI: direct link, hf CLI and curl.
- Browser
- Download file 51 Bytes
-
https://huggingface.co/arthursilvadantas/NotavelAI/resolve/main/classes.json
- Command line
-
hf download hf://arthursilvadantas/NotavelAI/classes.json
-
curl -L -o classes.json https://huggingface.co/arthursilvadantas/NotavelAI/resolve/main/classes.json
51 Bytes
| ["2", "5", "10", "20", "50", "100", "200", "fundo"] |