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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ansulev/OpenAI-Privacy-Filter") model = AutoModelForTokenClassification.from_pretrained("ansulev/OpenAI-Privacy-Filter", device_map="auto") - 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
Download tokenizer.json from ansulev/OpenAI-Privacy-Filter: direct link, hf CLI and curl.
- Browser
- Download file 27.9 MB
-
https://huggingface.co/ansulev/OpenAI-Privacy-Filter/resolve/main/tokenizer.json
- Command line
-
hf download hf://ansulev/OpenAI-Privacy-Filter/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ansulev/OpenAI-Privacy-Filter/resolve/main/tokenizer.json
27.9 MB
- Xet hash:
- 59f22360b51bf1a137fb80e14df310b4b249bed6cc64565aa0c401ca19ffcd04
- Size of remote file:
- 27.9 MB
- SHA256:
- 0614fe83cadab421296e664e1f48f4261fa8fef6e03e63bb75c20f38e37d07d3
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