🧠
Mpnet Use Combined No Pt model by victormuryn
⭐ 38.4
🧠
Model

Mpnet Use Combined No Pt

by victormuryn victormuryn/mpnet-use-combined-no-pt
Free2AITools Nexus Index
38.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 4
R: Recency 78
Q: Quality 65
Tech Context
0.28B Params
4.096K Ctx
Vital Performance
41 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 38.4 FNI Score
Tiny 0.28B Params
4k Context
41 Downloads
8G GPU ~2GB Est. VRAM
Dense XLMROBERTAMODEL Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID victormuryn/mpnet-use-combined-no-pt
License Apache-2.0
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{victormuryn_mpnet_use_combined_no_pt,
  author = {victormuryn},
  title = {Mpnet Use Combined No Pt Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/victormuryn/mpnet-use-combined-no-pt}},
  note = {Accessed via Free2AITools.}
}
APA Style
victormuryn. (2026). Mpnet Use Combined No Pt [Model]. Free2AITools. https://huggingface.co/victormuryn/mpnet-use-combined-no-pt

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run mpnet-use-combined-no-pt
πŸ€— HF Download
huggingface-cli download victormuryn/mpnet-use-combined-no-pt
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) 4
Recency (R) 78
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Mpnet Use Combined No Pt: Authority (A:0), Popularity (P:4), Recency (R:78), 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
41Downloads
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--victormuryn--mpnet-use-combined-no-pt
slug
victormuryn--mpnet-use-combined-no-pt
source
huggingface
author
victormuryn
license
Apache-2.0
tags
sentence-transformers, safetensors, xlm-roberta, feature-extraction, sentence-similarity, transformers, multilingual, ar, bg, ca, cs, da, de, el, en, es, et, fa, fi, fr, gl, gu, he, hi, hr, hu, hy, id, it, ja, ka, ko, ku, lt, lv, mk, mn, mr, ms, my, nb, nl, pl, pt, ro, sk, sl, sq, sr, sv, th, tr, uk, ur, vi, license:apache-2.0, text-embeddings-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
XLMRobertaModel
params billions
0.28
context length
4,096
pipeline tag
sentence-similarity
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
41

Data indexed from public sources. Updated daily.