🧠

Model

Roberta Base Japanese Char Luw Upos

Name: Roberta Base Japanese Char Luw Upos
Author: KoichiYasuoka

by KoichiYasuoka koichiyasuoka/roberta-base-japanese-char-luw-upos

Free2AITools Nexus Index

25.6

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29

P: Popularity 3

R: Recency 82

Q: Quality 50

Tech Context

512 Ctx

Vital Performance

23 DL / 30D

Source →

Technical Constraints

Experimental / High Latency

Low FNI signal 25.6 FNI Score

Tiny - Params

1k Context

23 Downloads

Dense ROBERTAFORTOKENCLASSIFICATION Architecture

Restricted CC License

Model Information Summary
Entity Passport
Registry ID	koichiyasuoka/roberta-base-japanese-char-luw-upos
License	CC-BY-SA-4.0
Provider	huggingface

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{koichiyasuoka_roberta_base_japanese_char_luw_upos,
  author = {KoichiYasuoka},
  title = {Roberta Base Japanese Char Luw Upos Model},
  year = {2022},
  howpublished = {\url{https://huggingface.co/KoichiYasuoka/roberta-base-japanese-char-luw-upos}},
  note = {Accessed via Free2AITools.}
}

APA Style

KoichiYasuoka. (2022). Roberta Base Japanese Char Luw Upos [Model]. Free2AITools. https://huggingface.co/KoichiYasuoka/roberta-base-japanese-char-luw-upos

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download

huggingface-cli download koichiyasuoka/roberta-base-japanese-char-luw-upos

📦 Install Lib

pip install -U transformers

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 29

Popularity (P) 3

Recency (R) 82

Quality (Q) 50

💬 Index Insight

FNI V2.0 for Roberta Base Japanese Char Luw Upos: Authority (A:29), Popularity (P:3), Recency (R:82), Quality (Q:50). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

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⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

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📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.

Social Proof

HuggingFace Hub

23Downloads

Hub Discussions

🤗 Data Source: Hugging Face ↗

🔄 Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--koichiyasuoka--roberta-base-japanese-char-luw-upos
slug: koichiyasuoka--roberta-base-japanese-char-luw-upos
source: huggingface
author: KoichiYasuoka
license: CC-BY-SA-4.0
tags: transformers, pytorch, roberta, token-classification, japanese, pos, dependency-parsing, ja, dataset:universal_dependencies, license:cc-by-sa-4.0, endpoints_compatible, region:us

⚙️ Technical Specs

architecture: RobertaForTokenClassification
context length: 512
pipeline tag: token-classification

📊 Engagement & Metrics

downloads: 23
stars: 0
forks: 0

Data indexed from public sources. Updated daily.