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Openmed Pii Portuguese Superclinical Base 184m V1 model by OpenMed
⭐ 39.2
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Model

Openmed Pii Portuguese Superclinical Base 184m V1

by OpenMed openmed/openmed-pii-portuguese-superclinical-base-184m-v1
Free2AITools Nexus Index
39.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 9
R: Recency 69
Q: Quality 65
Tech Context
0.18B Params
512 Ctx
Vital Performance
120 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.2 FNI Score
Tiny 0.18B Params
1k Context
120 Downloads
8G GPU ~2GB Est. VRAM
Dense DEBERTAV2FORTOKENCLASSIFICATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID openmed/openmed-pii-portuguese-superclinical-base-184m-v1
License Apache-2.0
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{openmed_openmed_pii_portuguese_superclinical_base_184m_v1,
  author = {OpenMed},
  title = {Openmed Pii Portuguese Superclinical Base 184m V1 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/OpenMed/OpenMed-PII-Portuguese-SuperClinical-Base-184M-v1}},
  note = {Accessed via Free2AITools.}
}
APA Style
OpenMed. (2026). Openmed Pii Portuguese Superclinical Base 184m V1 [Model]. Free2AITools. https://huggingface.co/OpenMed/OpenMed-PII-Portuguese-SuperClinical-Base-184M-v1

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run openmed-pii-portuguese-superclinical-base-184m-v1
πŸ€— HF Download
huggingface-cli download openmed/openmed-pii-portuguese-superclinical-base-184m-v1
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) 9
Recency (R) 69
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Openmed Pii Portuguese Superclinical Base 184m V1: Authority (A:0), Popularity (P:9), Recency (R:69), 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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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
120Downloads
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--openmed--openmed-pii-portuguese-superclinical-base-184m-v1
slug
openmed--openmed-pii-portuguese-superclinical-base-184m-v1
source
huggingface
author
OpenMed
license
Apache-2.0
tags
transformers, safetensors, deberta-v2, token-classification, ner, pii, pii-detection, de-identification, privacy, healthcare, medical, clinical, phi, portuguese, pytorch, openmed, pt, base_model:microsoft/deberta-v3-base, base_model:finetune:microsoft/deberta-v3-base, license:apache-2.0, model-index, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
DebertaV2ForTokenClassification
params billions
0.18
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
120

Data indexed from public sources. Updated daily.