Instructions to use ansulev/OpenAI-Privacy-Filter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ansulev/OpenAI-Privacy-Filter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ansulev/OpenAI-Privacy-Filter")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ansulev/OpenAI-Privacy-Filter") model = AutoModelForTokenClassification.from_pretrained("ansulev/OpenAI-Privacy-Filter") - Transformers.js
How to use ansulev/OpenAI-Privacy-Filter with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'ansulev/OpenAI-Privacy-Filter'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e7253031392ce49a58cdbb575538580977a8db635f4ad8f770dbd02a2c7d0cd
- Size of remote file:
- 143 kB
- SHA256:
- 04978ae127ae0922625319bfbf84b8664362ce32a1adc03414cf8215c3e2bc17
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