🧠
Deberta Base Combined Squad1 Aqa And Newsqa 1epoch model by stevemobs
⭐ 23.5
🧠
Model

Deberta Base Combined Squad1 Aqa And Newsqa 1epoch

by stevemobs hf-model--stevemobs--deberta-base-combined-squad1-aqa-and-newsqa-1epoch
Nexus Index
23.5 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 1
R: Recency 6
Q: Quality 50
Tech Context
Vital Performance
7 DL / 30D
0.0%
Source →
Audited 23.5 FNI Score
Tiny - Params
- Context
7 Downloads
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID hf-model--stevemobs--deberta-base-combined-squad1-aqa-and-newsqa-1epoch
License MIT
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__stevemobs__deberta_base_combined_squad1_aqa_and_newsqa_1epoch,
  author = {stevemobs},
  title = {Deberta Base Combined Squad1 Aqa And Newsqa 1epoch Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/stevemobs/deberta-base-combined-squad1-aqa-and-newsqa-1epoch}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
stevemobs. (2026). Deberta Base Combined Squad1 Aqa And Newsqa 1epoch [Model]. Free2AITools. https://huggingface.co/stevemobs/deberta-base-combined-squad1-aqa-and-newsqa-1epoch

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download stevemobs/deberta-base-combined-squad1-aqa-and-newsqa-1epoch
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
23.5
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 1
Recency (R) 6
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Deberta Base Combined Squad1 Aqa And Newsqa 1epoch: Semantic (S:50), Authority (A:0), Popularity (P:1), Recency (R:6), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

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

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📝 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
7Downloads
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--stevemobs--deberta-base-combined-squad1-aqa-and-newsqa-1epoch
slug
stevemobs--deberta-base-combined-squad1-aqa-and-newsqa-1epoch
source
huggingface
author
stevemobs
license
MIT
tags
transformers, pytorch, tensorboard, deberta, question-answering, generated_from_trainer, license:mit, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
question-answering

📊 Engagement & Metrics

downloads
7
stars
0
forks
0

Data indexed from public sources. Updated daily.