🧠
Xlm R Base Squad En 5k Lora Add V260719220438 model by alxxtexxr
⭐ 37.4
🧠
Model

Xlm R Base Squad En 5k Lora Add V260719220438

by alxxtexxr alxxtexxr/xlm-r-base-squad-en-5k-lora-add-v260719220438
Free2AITools Nexus Index
37.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 1
R: Recency 87
Q: Quality 65
Tech Context
0.28B Params
5.12K Ctx
Vital Performance
10 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37.4 FNI Score
Tiny 0.28B Params
5k Context
10 Downloads
8G GPU ~2GB Est. VRAM
Dense XLMROBERTAFORQUESTIONANSWERING Architecture
Model Information Summary
Entity Passport
Registry ID alxxtexxr/xlm-r-base-squad-en-5k-lora-add-v260719220438
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{alxxtexxr_xlm_r_base_squad_en_5k_lora_add_v260719220438,
  author = {alxxtexxr},
  title = {Xlm R Base Squad En 5k Lora Add V260719220438 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/alxxtexxr/XLM-R-Base-squad-en-5K-LoRA-add-v260719220438}},
  note = {Accessed via Free2AITools.}
}
APA Style
alxxtexxr. (2026). Xlm R Base Squad En 5k Lora Add V260719220438 [Model]. Free2AITools. https://huggingface.co/alxxtexxr/XLM-R-Base-squad-en-5K-LoRA-add-v260719220438

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run xlm-r-base-squad-en-5k-lora-add-v260719220438
πŸ€— HF Download
huggingface-cli download alxxtexxr/xlm-r-base-squad-en-5k-lora-add-v260719220438
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) 1
Recency (R) 87
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Xlm R Base Squad En 5k Lora Add V260719220438: Authority (A:0), Popularity (P:1), Recency (R:87), 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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
10Downloads
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--alxxtexxr--xlm-r-base-squad-en-5k-lora-add-v260719220438
slug
alxxtexxr--xlm-r-base-squad-en-5k-lora-add-v260719220438
source
huggingface
author
alxxtexxr
tags
transformers, safetensors, xlm-roberta, question-answering, arxiv:1910.09700, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
XLMRobertaForQuestionAnswering
params billions
0.28
context length
5,120
pipeline tag
question-answering
vram gb
1.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
10

Data indexed from public sources. Updated daily.