MODEL PROFILE · 模型档案

privacy-filter-multilingual

OpenMed · privacy-filter-multilingual

Fine-tuned `openai/privacy-filter` for **fine-grained PII extraction** across **54 categories** in **16 languages**. - **Base model**: `openai/privacy-filter` — 1.4B-parameter MoE (50M active per token), BIOES token-classification head - **Task**: Token classification for PII detection (BIOES scheme) - **Languages (16)**: Arabic, Bengali, Chinese, Dutch, English, French, German, Hindi, Italian, Japanese, Korean, Portuguese, Spanish, Telugu, Turkish, Vietnamese - **Training data**: Multilingual mix from AI4Privacy — `pii-masking-200k`, `pii-masking-400k`, and `open-pii-masking-500k-ai4privacy`, language-balanced - **Recipe**: `opf train` (OpenAI's official fine-tuning CLI) — full fine-tune, AdamW, balanced language sampling, 5 epochs, bf16 - **Labels**: 54 PII categories → 217 BIOES classes (1 `O` + 54 × B/I/E/S) The base model ships with 8 coarse PII categories and English-only training. This model trades that for a **6.75× more granular vocabulary** spanning identity, contact, address, financial, vehicle, digital, and crypto labels — all evaluated across 16 languages.

译文排队中,当前展示来源原文。

文本分析license:apache-2.0
上下文窗口来源未披露
输入 → 输出文本 → 文本
模型权重待核验
档案更新时间2026/10/29 14:28:52
OVERVIEW

模型介绍

Fine-tuned `openai/privacy-filter` for **fine-grained PII extraction** across **54 categories** in **16 languages**. - **Base model**: `openai/privacy-filter` — 1.4B-parameter MoE (50M active per token), BIOES token-classification head - **Task**: Token classification for PII detection (BIOES scheme) - **Languages (16)**: Arabic, Bengali, Chinese, Dutch, English, French, German, Hindi, Italian, Japanese, Korean, Portuguese, Spanish, Telugu, Turkish, Vietnamese - **Training data**: Multilingual mix from AI4Privacy — `pii-masking-200k`, `pii-masking-400k`, and `open-pii-masking-500k-ai4privacy`, language-balanced - **Recipe**: `opf train` (OpenAI's official fine-tuning CLI) — full fine-tune, AdamW, balanced language sampling, 5 epochs, bf16 - **Labels**: 54 PII categories → 217 BIOES classes (1 `O` + 54 × B/I/E/S) The base model ships with 8 coarse PII categories and English-only training. This model trades that for a **6.75× more granular vocabulary** spanning identity, contact, address, financial, vehicle, digital, and crypto labels — all evaluated across 16 languages.

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。

PRICING & COST

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。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价,请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

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。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用?

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗?

不是实时结算价格,而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

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。