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 generation_config.json from howwhenRaw/llm-for-sec-secjev: direct link, hf CLI and curl.
- Browser
- Download file 170 Bytes
-
https://huggingface.co/howwhenRaw/llm-for-sec-secjev/resolve/main/generation_config.json
- Command line
-
hf download hf://howwhenRaw/llm-for-sec-secjev/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/howwhenRaw/llm-for-sec-secjev/resolve/main/generation_config.json
170 Bytes
| { | |
| "do_sample": false, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "max_new_tokens": 2048, | |
| "pad_token_id": 151643, | |
| "transformers_version": "5.8.0" | |
| } | |