🧠
Flisak Anon En model by Kurdzik
⭐ 39.4
🧠
Model

Flisak Anon En

by Kurdzik kurdzik/flisak-anon-en
Free2AITools Nexus Index
39.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 3
R: Recency 100
Q: Quality 65
Tech Context
0.12B Params
512 Ctx
Vital Performance
29 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.4 FNI Score
Tiny 0.12B Params
1k Context
29 Downloads
8G GPU ~2GB Est. VRAM
Dense ROBERTAFORTOKENCLASSIFICATION Architecture
Restricted CC License
Model Information Summary
Entity Passport
Registry ID kurdzik/flisak-anon-en
License CC-BY-4.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{kurdzik_flisak_anon_en,
  author = {Kurdzik},
  title = {Flisak Anon En Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Kurdzik/flisak-anon-en}},
  note = {Accessed via Free2AITools.}
}
APA Style
Kurdzik. (2026). Flisak Anon En [Model]. Free2AITools. https://huggingface.co/Kurdzik/flisak-anon-en

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run flisak-anon-en
πŸ€— HF Download
huggingface-cli download kurdzik/flisak-anon-en
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) 0
Popularity (P) 3
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Flisak Anon En: Authority (A:0), Popularity (P:3), Recency (R:100), Quality (Q:65). 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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πŸš€ What's Next?

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Deployment reference

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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
29Downloads
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--kurdzik--flisak-anon-en
slug
kurdzik--flisak-anon-en
source
huggingface
author
Kurdzik
license
CC-BY-4.0
tags
transformers, pytorch, safetensors, roberta, token-classification, ner, anonymization, pii, english, en, dataset:nvidia/nemotron-pii, dataset:multiconer/multiconer_v2, dataset:gatenlp/broad_twitter_corpus, arxiv:1907.11692, base_model:facebookai/roberta-base, base_model:finetune:facebookai/roberta-base, license:cc-by-4.0, model-index, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
RobertaForTokenClassification
params billions
0.12
context length
512
pipeline tag
token-classification
vram gb
1.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
29

Data indexed from public sources. Updated daily.