Instructions to use lol-cod/captchasolving with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use lol-cod/captchasolving with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://lol-cod/captchasolving") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a081ad7b5f47e42e2b545644ecb746f707a25752c33fd33c786a7e41bdf1ea8
- Size of remote file:
- 6.1 MB
- SHA256:
- e1f47afe0f72e89ee5b7100c212b03943c405a60a0b94690d66022eeaec47ccd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.