🧠
Robertalexpt Base model by eduagarcia
⭐ 25.1
🧠
Model

Robertalexpt Base

by eduagarcia eduagarcia/robertalexpt-base
Free2AITools Nexus Index
25.1
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 48
P: Popularity 21
R: Recency 18
Q: Quality 65
Tech Context
0.12B Params
512 Ctx
Vital Performance
566 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 25.1 FNI Score
Tiny 0.12B Params
1k Context
566 Downloads
8G GPU ~2GB Est. VRAM
Dense ROBERTAFORMASKEDLM Architecture
Restricted CC License
Model Information Summary
Entity Passport
Registry ID eduagarcia/robertalexpt-base
License CC-BY-4.0
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{eduagarcia_robertalexpt_base,
  author = {eduagarcia},
  title = {Robertalexpt Base Model},
  year = {2024},
  howpublished = {\url{https://huggingface.co/eduagarcia/RoBERTaLexPT-base}},
  note = {Accessed via Free2AITools.}
}
APA Style
eduagarcia. (2024). Robertalexpt Base [Model]. Free2AITools. https://huggingface.co/eduagarcia/RoBERTaLexPT-base

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run robertalexpt-base
πŸ€— HF Download
huggingface-cli download eduagarcia/robertalexpt-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) 48
Popularity (P) 21
Recency (R) 18
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Robertalexpt Base: Authority (A:48), Popularity (P:21), Recency (R:18), 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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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
566Downloads
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--eduagarcia--robertalexpt-base
slug
eduagarcia--robertalexpt-base
source
huggingface
author
eduagarcia
license
CC-BY-4.0
tags
transformers, pytorch, safetensors, roberta, fill-mask, legal, pt, dataset:eduagarcia/legalpt_dedup, dataset:eduagarcia/crawlpt_dedup, license:cc-by-4.0, model-index, endpoints_compatible, deploy:azure, region:us

βš™οΈ Technical Specs

architecture
RobertaForMaskedLM
params billions
0.12
context length
512
pipeline tag
fill-mask
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
566
stars
0
forks
0

Data indexed from public sources. Updated daily.