Instructions to use rishab1090/potato with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use rishab1090/potato with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://rishab1090/potato") - Notebooks
- Google Colab
- Kaggle
| FROM python:3.10-slim | |
| WORKDIR /app | |
| COPY . . | |
| RUN pip install --upgrade pip | |
| RUN pip install -r requirements.txt | |
| CMD ["uvicorn", "backend:app", "--host", "0.0.0.0", "--port", "10000"] | |