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") - 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:
- 1eb7357fbd12a8de35fe8a15fd6712059f5302c7a8c6313f1824811fe5d6bc81
- Size of remote file:
- 1.9 GB
- SHA256:
- 4c12392ea557a904af3ced6f7c736d1a68b265e65e4a1b310fe0cec5c9e7424c
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