Instructions to use sumitranjan/PromptShield with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use sumitranjan/PromptShield 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://sumitranjan/PromptShield") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sumitranjan/PromptShield: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/sumitranjan/PromptShield/resolve/3f7d00a3aaacabc61336ba878aee0bb693d0acbc/tokenizer.json
- Command line
-
hf download hf://sumitranjan/PromptShield@3f7d00a3aaacabc61336ba878aee0bb693d0acbc/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/sumitranjan/PromptShield/resolve/3f7d00a3aaacabc61336ba878aee0bb693d0acbc/tokenizer.json
17.1 MB
- Xet hash:
- 7f686e947e0b9d36c958512a852baddaabd2b3ff5be7abad2fb11a1fb2755fe1
- Size of remote file:
- 17.1 MB
- SHA256:
- a514807cffabd8abaf028cfaffe7ff0c4f60b97ea2db80c41f14172ae6b018ca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.