Instructions to use NAMAA-Space/Ara-Prompt-Guard_V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NAMAA-Space/Ara-Prompt-Guard_V0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NAMAA-Space/Ara-Prompt-Guard_V0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NAMAA-Space/Ara-Prompt-Guard_V0") model = AutoModelForSequenceClassification.from_pretrained("NAMAA-Space/Ara-Prompt-Guard_V0", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from NAMAA-Space/Ara-Prompt-Guard_V0: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/NAMAA-Space/Ara-Prompt-Guard_V0/resolve/main/tokenizer.json
- Command line
-
hf download hf://NAMAA-Space/Ara-Prompt-Guard_V0/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/NAMAA-Space/Ara-Prompt-Guard_V0/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 95d201491a209c27f166e8c9ab0889bcf79d09f517d38492d126f17f204005c1
- Size of remote file:
- 16.3 MB
- SHA256:
- 9def354f6950033f73fe0208a0f425adb407f5e3659cf9797e0c26a330339a6f
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