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Ultrabert 380m model by Dmis Lab
⭐ 40
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Model

Ultrabert 380m

by Dmis Lab dmis-lab/ultrabert-380m
Free2AITools Nexus Index
40.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 39
P: Popularity 8
R: Recency 99
Q: Quality 65
Tech Context
0.43B Params
4.096K Ctx
Vital Performance
101 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 40 FNI Score
Tiny 0.43B Params
4k Context
101 Downloads
8G GPU ~2GB Est. VRAM
Dense ULTRABERTFORMASKEDLM Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID dmis-lab/ultrabert-380m
License Apache-2.0
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{dmis_lab_ultrabert_380m,
  author = {Dmis Lab},
  title = {Ultrabert 380m Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/dmis-lab/UltraBERT-380M}},
  note = {Accessed via Free2AITools.}
}
APA Style
Dmis Lab. (2026). Ultrabert 380m [Model]. Free2AITools. https://huggingface.co/dmis-lab/UltraBERT-380M

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run ultrabert-380m
πŸ€— HF Download
huggingface-cli download dmis-lab/ultrabert-380m
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) 39
Popularity (P) 8
Recency (R) 99
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Ultrabert 380m: Authority (A:39), Popularity (P:8), Recency (R:99), 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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⚠️ 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
101Downloads
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--dmis-lab--ultrabert-380m
slug
dmis-lab--ultrabert-380m
source
huggingface
author
Dmis Lab
license
Apache-2.0
tags
transformers, safetensors, ultrabert, fill-mask, encoder, masked-language-modeling, long-context, custom_code, en, dataset:mlfoundations/dclm-baseline-1.0, dataset:huggingfacefw/fineweb-edu, dataset:huggingfacetb/stack-edu, dataset:allenai/pes2o, dataset:llm360/megamath, dataset:huggingfacetb/finemath, dataset:huggingfacetb/smollm-corpus, dataset:allenai/dolma, dataset:open-orca/flan, dataset:facebook/natural_reasoning, license:apache-2.0, region:us

βš™οΈ Technical Specs

architecture
UltrabertForMaskedLM
params billions
0.43
context length
4,096
pipeline tag
fill-mask
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
101

Data indexed from public sources. Updated daily.