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

Mdeberta V3 Base 2e 05 Viepaws

by ngwgsang ngwgsang/mdeberta-v3-base-2e-05-viepaws
Free2AITools Nexus Index
39.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 3
R: Recency 88
Q: Quality 65
Tech Context
0.28B Params
512 Ctx
Vital Performance
24 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.3 FNI Score
Tiny 0.28B Params
1k Context
24 Downloads
8G GPU ~2GB Est. VRAM
Dense DEBERTAV2FORSEQUENCECLASSIFICATION Architecture
Model Information Summary
Entity Passport
Registry ID ngwgsang/mdeberta-v3-base-2e-05-viepaws
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{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.}
}
APA Style
ngwgsang. (2026). Mdeberta V3 Base 2e 05 Viepaws [Model]. Free2AITools. https://huggingface.co/ngwgsang/mdeberta-v3-base-2e-05-viepaws

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run mdeberta-v3-base-2e-05-viepaws
πŸ€— HF Download
huggingface-cli download ngwgsang/mdeberta-v3-base-2e-05-viepaws
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) 88
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Mdeberta V3 Base 2e 05 Viepaws: Authority (A:0), Popularity (P:3), Recency (R:88), 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
---

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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
24Downloads
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--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

βš™οΈ Technical Specs

architecture
DebertaV2ForSequenceClassification
params billions
0.28
context length
512
pipeline tag
text-classification
vram gb
1.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
24
stars
null
forks
null

Data indexed from public sources. Updated daily.