attackgeneration-toxicity_gpt2

模型介绍

**This adversarial model has a propensity to produce highly unsavoury content from the outset. It is not intended or suitable for general use or human consumption.** This special-use model aims to provide prompts that goad LLMs into producting "toxicity". Toxicity here is defined by the content of the Civil Comments dataset, containing categories such as `obscene`, `threat`, `insult`, `identity_attack`, `sexual_explicit` and `severe_toxicity`. For details, see the description of the Jigsaw 2019 data. The base model is the community version of gpt2 with ~125M parameters. This model is not aligned and is "noisy" relative to more advanced models. Both the lack of alignment and the existence of noise are favourable to the task of trying to goad other models into producing unsafe output: unsafe prompts have a propensity to yield unsafe outputs, and noisy behaviour can lead to a broader exploration of input space.

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。