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Xlm Roberta Base Finetuned Est model by eglesaks
⭐ 23.4
🧠
Model

Xlm Roberta Base Finetuned Est

by eglesaks eglesaks/xlm-roberta-base-finetuned-est
Free2AITools Nexus Index
23.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 2
R: Recency 4
Q: Quality 50
Tech Context
Vital Performance
14 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 23.4 FNI Score
Tiny - Params
- Context
14 Downloads
Dense XLMROBERTAFORQUESTIONANSWERING Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID eglesaks/xlm-roberta-base-finetuned-est
License MIT
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{eglesaks_xlm_roberta_base_finetuned_est,
  author = {eglesaks},
  title = {Xlm Roberta Base Finetuned Est Model},
  year = {2022},
  howpublished = {\url{https://huggingface.co/eglesaks/xlm-roberta-base-finetuned-est}},
  note = {Accessed via Free2AITools.}
}
APA Style
eglesaks. (2022). Xlm Roberta Base Finetuned Est [Model]. Free2AITools. https://huggingface.co/eglesaks/xlm-roberta-base-finetuned-est

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download eglesaks/xlm-roberta-base-finetuned-est
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) 0
Popularity (P) 2
Recency (R) 4
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Xlm Roberta Base Finetuned Est: Authority (A:0), Popularity (P:2), Recency (R:4), Quality (Q:50). 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
14Downloads
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--eglesaks--xlm-roberta-base-finetuned-est
slug
eglesaks--xlm-roberta-base-finetuned-est
source
huggingface
author
eglesaks
license
MIT
tags
transformers, pytorch, tensorboard, xlm-roberta, question-answering, generated_from_trainer, license:mit, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
XLMRobertaForQuestionAnswering
pipeline tag
question-answering

πŸ“Š Engagement & Metrics

downloads
14
stars
0
forks
0

Data indexed from public sources. Updated daily.