🧠
Meteorite Dinov2 B14 Direct model by Eki734
⭐ 37.5
🧠
Model

Meteorite Dinov2 B14 Direct

by Eki734 eki734/meteorite-dinov2-b14-direct
Free2AITools Nexus Index
37.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 5
R: Recency 83
Q: Quality 50
Tech Context
2 Params
4.096K Ctx
Vital Performance
46 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37.5 FNI Score
Tiny 2B Params
4k Context
46 Downloads
8G GPU ~3GB Est. VRAM
Dense METEORITEDINOFORIMAGECLASSIFICATION Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID eki734/meteorite-dinov2-b14-direct
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{eki734_meteorite_dinov2_b14_direct,
  author = {Eki734},
  title = {Meteorite Dinov2 B14 Direct Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Eki734/meteorite-dinov2-b14-direct}},
  note = {Accessed via Free2AITools.}
}
APA Style
Eki734. (2026). Meteorite Dinov2 B14 Direct [Model]. Free2AITools. https://huggingface.co/Eki734/meteorite-dinov2-b14-direct

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run meteorite-dinov2-b14-direct
πŸ€— HF Download
huggingface-cli download eki734/meteorite-dinov2-b14-direct
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) 5
Recency (R) 83
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Meteorite Dinov2 B14 Direct: Authority (A:0), Popularity (P:5), Recency (R:83), 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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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.

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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
46Downloads
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--eki734--meteorite-dinov2-b14-direct
slug
eki734--meteorite-dinov2-b14-direct
source
huggingface
author
Eki734
license
MIT
tags
transformers, pytorch, meteorite_dinov2_probe, image-classification, dinov2, meteorite, custom_code, license:mit, region:us

βš™οΈ Technical Specs

architecture
MeteoriteDinoForImageClassification
params billions
2
context length
4,096
pipeline tag
image-classification
vram gb
2.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
46

Data indexed from public sources. Updated daily.