🧠
Bart Base model by facebook
⭐ 35.8
🧠
Model

Bart Base

by facebook facebook/bart-base
Free2AITools Nexus Index
35.8
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 55
P: Popularity 71
R: Recency 6
Q: Quality 65
Tech Context
0.14B Params
1.024K Ctx
Vital Performance
1.8M DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 35.8 FNI Score
Tiny 0.14B Params
1k Context
Hot 1.8M Downloads
8G GPU ~2GB Est. VRAM
Dense BARTMODEL Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID facebook/bart-base
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{facebook_bart_base,
  author = {facebook},
  title = {Bart Base Model},
  year = {2022},
  howpublished = {\url{https://huggingface.co/facebook/bart-base}},
  note = {Accessed via Free2AITools.}
}
APA Style
facebook. (2022). Bart Base [Model]. Free2AITools. https://huggingface.co/facebook/bart-base

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run bart-base
πŸ€— HF Download
huggingface-cli download facebook/bart-base
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) 55
Popularity (P) 71
Recency (R) 6
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Bart Base: Authority (A:55), Popularity (P:71), Recency (R:6), 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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Deployment reference

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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.

Social Proof

HuggingFace Hub
1.8MDownloads
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--facebook--bart-base
slug
facebook--bart-base
source
huggingface
author
facebook
license
Apache-2.0
tags
transformers, pytorch, tf, jax, safetensors, bart, feature-extraction, en, arxiv:1910.13461, license:apache-2.0, endpoints_compatible, deploy:azure, region:us

βš™οΈ Technical Specs

architecture
BartModel
params billions
0.14
context length
1,024
pipeline tag
feature-extraction
vram gb
1.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
1,814,203
stars
0
forks
0

Data indexed from public sources. Updated daily.