🧠
Msmarco Bert Base Dot V5 model by Sentence Transformers
⭐ 40.7
🧠
Model

Msmarco Bert Base Dot V5

by Sentence Transformers sentence-transformers/msmarco-bert-base-dot-v5
Free2AITools Nexus Index
40.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 48
P: Popularity 68
R: Recency 39
Q: Quality 65
Tech Context
0.11B Params
512 Ctx
Vital Performance
822.8K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 40.7 FNI Score
Tiny 0.11B Params
1k Context
Hot 822.8K Downloads
8G GPU ~2GB Est. VRAM
Dense BERTMODEL Architecture
Model Information Summary
Entity Passport
Registry ID sentence-transformers/msmarco-bert-base-dot-v5
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{sentence_transformers_msmarco_bert_base_dot_v5,
  author = {Sentence Transformers},
  title = {Msmarco Bert Base Dot V5 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/sentence-transformers/msmarco-bert-base-dot-v5}},
  note = {Accessed via Free2AITools.}
}
APA Style
Sentence Transformers. (2026). Msmarco Bert Base Dot V5 [Model]. Free2AITools. https://huggingface.co/sentence-transformers/msmarco-bert-base-dot-v5

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run msmarco-bert-base-dot-v5
πŸ€— HF Download
huggingface-cli download sentence-transformers/msmarco-bert-base-dot-v5
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) 68
Recency (R) 39
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Msmarco Bert Base Dot V5: Authority (A:48), Popularity (P:68), Recency (R:39), 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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
822.8KDownloads
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--sentence-transformers--msmarco-bert-base-dot-v5
slug
sentence-transformers--msmarco-bert-base-dot-v5
source
huggingface
author
Sentence Transformers
license
tags
sentence-transformers, pytorch, tf, onnx, safetensors, openvino, bert, feature-extraction, sentence-similarity, transformers, en, arxiv:1908.10084, text-embeddings-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
BertModel
params billions
0.11
context length
512
pipeline tag
sentence-similarity
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
822,837
stars
0
forks
0

Data indexed from public sources. Updated daily.