Instructions to use mlx-community/openai-privacy-filter-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/openai-privacy-filter-6bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/openai-privacy-filter-6bit --local-dir openai-privacy-filter-6bit
- Transformers.js
How to use mlx-community/openai-privacy-filter-6bit with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'mlx-community/openai-privacy-filter-6bit'); - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer_config.json from mlx-community/openai-privacy-filter-6bit: direct link, hf CLI and curl.
- Browser
- Download file 283 Bytes
-
https://huggingface.co/mlx-community/openai-privacy-filter-6bit/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://mlx-community/openai-privacy-filter-6bit/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/mlx-community/openai-privacy-filter-6bit/resolve/main/tokenizer_config.json
283 Bytes
| { | |
| "backend": "tokenizers", | |
| "eos_token": "<|endoftext|>", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 128000, | |
| "pad_token": "<|endoftext|>", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |