🧠
SecureBERT model by ehsanaghaei
⭐ 40.1
🧠
Model

SecureBERT

by ehsanaghaei ehsanaghaei/securebert
Free2AITools Nexus Index
40.1
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 52
P: Popularity 51
R: Recency 54
Q: Quality 50
Tech Context
512 Ctx
Vital Performance
29.3K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 40.1 FNI Score
Tiny - Params
1k Context
29.3K Downloads
Dense ROBERTAFORMASKEDLM Architecture
Restricted BIGSCIENCE License
Model Information Summary
Entity Passport
Registry ID ehsanaghaei/securebert
License BigScience-OpenRAIL-M
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{ehsanaghaei_securebert,
  author = {ehsanaghaei},
  title = {SecureBERT Model},
  year = {2022},
  howpublished = {\url{https://huggingface.co/ehsanaghaei/SecureBERT}},
  note = {Accessed via Free2AITools.}
}
APA Style
ehsanaghaei. (2022). SecureBERT [Model]. Free2AITools. https://huggingface.co/ehsanaghaei/SecureBERT

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download ehsanaghaei/securebert
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 52
Popularity (P) 51
Recency (R) 54
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for SecureBERT: Authority (A:52), Popularity (P:51), Recency (R:54), 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
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

Technical Deep Dive

⚠️ Incomplete Data

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

View Original Source β†’

πŸ“ Limitations & Considerations

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

Social Proof

HuggingFace Hub
29.3KDownloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

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

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--ehsanaghaei--securebert
slug
ehsanaghaei--securebert
source
huggingface
author
ehsanaghaei
license
BigScience-OpenRAIL-M
tags
transformers, pytorch, roberta, fill-mask, cybersecurity, cyber threat intelligence, en, base_model:facebookai/roberta-base, base_model:finetune:facebookai/roberta-base, doi:10.57967/hf/0042, license:bigscience-openrail-m, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
RobertaForMaskedLM
context length
512
pipeline tag
fill-mask

πŸ“Š Engagement & Metrics

downloads
29,259
stars
0
forks
0

Data indexed from public sources. Updated daily.