Text Classification
jev-style
Safetensors
Chinese
English
qwen3
security
decision-model
safety-perception
lora
Instructions to use howwhenRaw/llm-for-sec-secjev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- jev-style
How to use howwhenRaw/llm-for-sec-secjev with jev-style:
pip install "jev-style[torch]"
from jev_style import JevStyle, noul, choice js = JevStyle.from_pretrained("howwhenRaw/llm-for-sec-secjev") out = js.decide("I was charged twice for one order.", { "billing": noul("This message is about billing."), "team": choice("Which team should handle it?", ["billing", "shipping", "tech"]), }) print(out["answers"]["team"]["choice"]) - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from howwhenRaw/llm-for-sec-secjev: direct link, hf CLI and curl.
- Browser
- Download file 750 Bytes
-
https://huggingface.co/howwhenRaw/llm-for-sec-secjev/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://howwhenRaw/llm-for-sec-secjev/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/howwhenRaw/llm-for-sec-secjev/resolve/main/tokenizer_config.json
750 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<|object_ref_start|>", | |
| "<|object_ref_end|>", | |
| "<|box_start|>", | |
| "<|box_end|>", | |
| "<|quad_start|>", | |
| "<|quad_end|>", | |
| "<|vision_start|>", | |
| "<|vision_end|>", | |
| "<|vision_pad|>", | |
| "<|image_pad|>", | |
| "<|video_pad|>" | |
| ], | |
| "is_local": true, | |
| "local_files_only": true, | |
| "model_max_length": 131072, | |
| "pad_token": "<|endoftext|>", | |
| "padding_side": "right", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |