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:
- 3620c7a7fa342105f181c0256293b2f05c63e7d56d684da9d10a640392bbe3d4
- Size of remote file:
- 1.91 GB
- SHA256:
- b5f641c184d5caf50ad9c026efbc019c14cc528a07491a1c500fd34c983d548f
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