Instructions to use Jibbscript/privacy-filter-oai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jibbscript/privacy-filter-oai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jibbscript/privacy-filter-oai")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jibbscript/privacy-filter-oai") model = AutoModelForTokenClassification.from_pretrained("Jibbscript/privacy-filter-oai") - Transformers.js
How to use Jibbscript/privacy-filter-oai with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'Jibbscript/privacy-filter-oai'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60e933884ada3bc98bb5e1d3660d98d192135c17ed05d647990aaa6f91f46d44
- Size of remote file:
- 166 kB
- SHA256:
- eaae4e83cf1345a60abe333ed882b55fe5775d1dfbf34b9b269e5e5416f45e5b
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