🧠
Model

Uae Large V1

by WhereIsAI whereisai/uae-large-v1
Free2AITools Nexus Index
42.1
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 55
P: Popularity 72
R: Recency 52
Q: Quality 65
Tech Context
0.34B Params
512 Ctx
Vital Performance
2.6M DL / 30D

Technical Constraints

Experimental / High Latency
Low FNI signal 42.1 FNI Score
Tiny 0.34B Params
1k Context
Hot 2.6M Downloads
8G GPU ~2GB Est. VRAM
Dense BERTMODEL Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID whereisai/uae-large-v1
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.6GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX
@misc{whereisai_uae_large_v1,
  author = {WhereIsAI},
  title = {Uae Large V1 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/WhereIsAI/UAE-Large-V1}},
  note = {Accessed via Free2AITools.}
}
APA Style
WhereIsAI. (2026). Uae Large V1 [Model]. Free2AITools. https://huggingface.co/WhereIsAI/UAE-Large-V1

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run uae-large-v1
πŸ€— HF Download
huggingface-cli download whereisai/uae-large-v1
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 55
Popularity (P) 72
Recency (R) 52
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Uae Large V1: Authority (A:55), Popularity (P:72), Recency (R:52), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

Open data Updated: Live data
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πŸš€ What's Next?

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
2.6MDownloads
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--whereisai--uae-large-v1
slug
whereisai--uae-large-v1
source
huggingface
author
WhereIsAI
license
MIT
tags
sentence-transformers, onnx, safetensors, openvino, bert, feature-extraction, mteb, sentence_embedding, feature_extraction, transformers, transformers.js, en, arxiv:2309.12871, license:mit, model-index, text-embeddings-inference, endpoints_compatible, deploy:azure, region:us

βš™οΈ Technical Specs

architecture
BertModel
params billions
0.34
context length
512
pipeline tag
feature-extraction
vram gb
1.6
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
2,593,451
stars
0
forks
0

Data indexed from public sources. Updated daily.