Instructions to use MuVeraAI/privacy-filter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MuVeraAI/privacy-filter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MuVeraAI/privacy-filter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MuVeraAI/privacy-filter") model = AutoModelForTokenClassification.from_pretrained("MuVeraAI/privacy-filter", device_map="auto") - Transformers.js
How to use MuVeraAI/privacy-filter with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'MuVeraAI/privacy-filter'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ac22ec0e6346fc3fe29671265eb5e3135cb47adfc1ed9a5dc316d782594e525
- Size of remote file:
- 917 MB
- SHA256:
- f30998e28c71c5374cc7e8b7de8f0f83e981592c0c2d652d2ad4928454dbb496
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