Instructions to use CapstoneML/Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use CapstoneML/Model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://CapstoneML/Model") - Notebooks
- Google Colab
- Kaggle
| location = { | |
| "Benteng Vredeburg": "https://surli.cc/bffath", | |
| "Candi Borobudur": "https://surl.lu/rqoiya", | |
| "Candi Prambanan": "https://surl.lu/evjzzc", | |
| "Gedung Agung Istana Kepresidenan": "https://surl.li/czgmti", | |
| "Masjid Gedhe Kauman": "https://surl.li/wpatgm", | |
| "Monumen Serangan 1 Maret": "https://surl.lu/axmfwy", | |
| "Museum Gunungapi Merapi": "https://surl.lu/wnkqof", | |
| "Situs Ratu Boko": "https://surl.li/abdxrb", | |
| "Taman Sari": "https://surl.li/rwpdyu", | |
| "Tugu Yogyakarta": "https://surl.li/tnehjk" | |
| } |