bert base japanese v3 ner wikipedia dataset EU AI Act Compliance Profile
llm-book
Your risk depends on how you use bert base japanese v3 ner wikipedia dataset
| Usage Context | Risk Level | Obligations |
|---|---|---|
| Internal coding tool | MINIMAL | 3 obligations (~12h) |
| Customer support bot | LIMITED | 7 obligations (~32h) |
| HR screening / hiring | HIGH | 19 obligations (~120h) |
| Credit decisions | HIGH | 19 obligations (~120h) |
| Medical triage | HIGH | 19 obligations (~120h) |
Why this tool is classified as MINIMAL
bert base japanese v3 ner wikipedia dataset is a token classification model by llm-book. Built with transformers. Supports ja. Licensed under apache-2.0. 16.2K downloads on HuggingFace.
Applicable Articles
Who does what
llm-book (provider)Their job
- Provider obligations being compiled
Risk Assessment Reasoning
This model is classified as Minimal Risk under the EU AI Act. No mandatory compliance obligations apply, but voluntary codes of practice are encouraged. AI literacy training (Art. 4) is recommended for all deployers.
Similar Models
Frequently Asked Questions
What is bert base japanese v3 ner wikipedia dataset's EU AI Act risk classification?
+
bert base japanese v3 ner wikipedia dataset is classified as MINIMAL under the EU AI Act.
What are my obligations if I deploy bert base japanese v3 ner wikipedia dataset?
+
As a bert base japanese v3 ner wikipedia dataset deployer, you have 1 base obligations (~8 hours estimated effort). Key articles: Art. 4.
What is bert base japanese v3 ner wikipedia dataset?
+
bert base japanese v3 ner wikipedia dataset is a Token Classification model by llm-book. It has 16.2K downloads on HuggingFace. Licensed under apache-2.0.
What are the EU AI Act deadlines for bert base japanese v3 ner wikipedia dataset?
+
Already passed: AI Literacy (Art. 4) — 2025-02-02.
Check bert base japanese v3 ner wikipedia dataset compliance in your codebase
One command to scan. Open-source CLI.