Text Classification
Transformers
ONNX
Safetensors
Transformers.js
English
bert
Intel
Eval Results (legacy)
text-embeddings-inference
Instructions to use kzt005/polite-guard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kzt005/polite-guard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kzt005/polite-guard")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kzt005/polite-guard") model = AutoModelForSequenceClassification.from_pretrained("kzt005/polite-guard", device_map="auto") - Transformers.js
How to use kzt005/polite-guard with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'kzt005/polite-guard'); - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from kzt005/polite-guard: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/kzt005/polite-guard/resolve/main/tokenizer.json
- Command line
-
hf download hf://kzt005/polite-guard/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/kzt005/polite-guard/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.