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:
- 330c0420a24e82791092f875f278e4f37526d7c3dcee7d101f1f0ecfcb0dd680
- Size of remote file:
- 6.68 MB
- SHA256:
- e6225fcbcb17b23c9054e47c4be419f1df58e95777296aaad64cdb6255add40e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.