🧠
Mdeberta V3 Base 2e 05 Viepaws model by ngwgsang
⭐ 39.3
🧠
Model

Mdeberta V3 Base 2e 05 Viepaws

by ngwgsang hf-model--ngwgsang--mdeberta-v3-base-2e-05-viepaws
Nexus Index
39.3 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 3
R: Recency 98
Q: Quality 65
Tech Context
3 Params
4.096K Ctx
Vital Performance
24 DL / 30D
0.0%
Source →
Audited 39.3 FNI Score
3B Params
4k Context
24 Downloads
8G GPU ~4GB Est. VRAM
Model Information Summary
Entity Passport
Registry ID hf-model--ngwgsang--mdeberta-v3-base-2e-05-viepaws
Provider huggingface
💾

Compute Threshold

~3.5GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__ngwgsang__mdeberta_v3_base_2e_05_viepaws,
  author = {ngwgsang},
  title = {Mdeberta V3 Base 2e 05 Viepaws Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ngwgsang/mdeberta-v3-base-2e-05-viepaws}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
ngwgsang. (2026). Mdeberta V3 Base 2e 05 Viepaws [Model]. Free2AITools. https://huggingface.co/ngwgsang/mdeberta-v3-base-2e-05-viepaws

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run mdeberta-v3-base-2e-05-viepaws
🤗 HF Download
huggingface-cli download ngwgsang/mdeberta-v3-base-2e-05-viepaws
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
39.3
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 3
Recency (R) 98
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Mdeberta V3 Base 2e 05 Viepaws: Semantic (S:50), Authority (A:0), Popularity (P:3), Recency (R:98), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
---

🚀 What's Next?

📊

Find Training Datasets

Discover datasets compatible with this model

📈

Compare Benchmarks

See how this model ranks on standard tests

⚡

Deployment Guide

Understand deployment options

Technical Deep Dive

⚠ī¸ 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 →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
24Downloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--ngwgsang--mdeberta-v3-base-2e-05-viepaws
slug
ngwgsang--mdeberta-v3-base-2e-05-viepaws
source
huggingface
author
ngwgsang
license
tags
transformers, safetensors, deberta-v2, text-classification, arxiv:1910.09700, text-embeddings-inference, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
3
context length
4,096
pipeline tag
text-classification
vram gb
3.5
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
24
stars
0
forks
0

Data indexed from public sources. Updated daily.