Image Classification
Keras
Korean
tensorflow
computer-vision
korean
secondhand-market
e-commerce
ensemble
Instructions to use bihan3876/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use bihan3876/my_model 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://bihan3876/my_model") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add YAML metadata to model cardโ
- Add license, language, tags for better discoverability - Include model type, pipeline tag, and base models - Fix Hugging Face metadata warningcdc112c -
Add Korean secondhand market AI classification models with Git LFSโ
- 70.61% accuracy ensemble model (7 models) - Python FastAPI server for image classification - Support 5 categories: ๊ฐ๊ตฌ, ์ํ์ฉํ, ์ ์๊ธฐ๊ธฐ_๋์, ์ทจ๋ฏธ_๊ฒ์, ํจ์ _๋ทฐํฐ - Total model size: 349MB (using Git LFS for .keras files)e310878
-
initial commit
Verified signature9f13643