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Convnext Tiny.in12k Ft In1k Finetuned Eurosat model by Taozhiyaoyao1
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Model

Convnext Tiny.in12k Ft In1k Finetuned Eurosat

by Taozhiyaoyao1 taozhiyaoyao1/convnext_tiny.in12k_ft_in1k-finetuned-eurosat
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 9
R: Recency 72
Q: Quality 65
Tech Context
0.03B Params
12.288K Ctx
Vital Performance
114 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 0.03B Params
12k Context
114 Downloads
8G GPU ~3GB Est. VRAM
Dense TIMMWRAPPERFORIMAGECLASSIFICATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID taozhiyaoyao1/convnext_tiny.in12k_ft_in1k-finetuned-eurosat
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{taozhiyaoyao1_convnext_tiny_in12k_ft_in1k_finetuned_eurosat,
  author = {Taozhiyaoyao1},
  title = {Convnext Tiny.in12k Ft In1k Finetuned Eurosat Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Taozhiyaoyao1/convnext_tiny.in12k_ft_in1k-finetuned-eurosat}},
  note = {Accessed via Free2AITools.}
}
APA Style
Taozhiyaoyao1. (2026). Convnext Tiny.in12k Ft In1k Finetuned Eurosat [Model]. Free2AITools. https://huggingface.co/Taozhiyaoyao1/convnext_tiny.in12k_ft_in1k-finetuned-eurosat

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run convnext_tiny.in12k_ft_in1k-finetuned-eurosat
πŸ€— HF Download
huggingface-cli download taozhiyaoyao1/convnext_tiny.in12k_ft_in1k-finetuned-eurosat
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) 9
Recency (R) 72
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Convnext Tiny.in12k Ft In1k Finetuned Eurosat: Authority (A:0), Popularity (P:9), Recency (R:72), 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
114Downloads
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--taozhiyaoyao1--convnext_tiny.in12k_ft_in1k-finetuned-eurosat
slug
taozhiyaoyao1--convnext_tiny.in12k_ft_in1k-finetuned-eurosat
source
huggingface
author
Taozhiyaoyao1
license
Apache-2.0
tags
transformers, safetensors, timm_wrapper, image-classification, timm, generated_from_trainer, base_model:timm/convnext_tiny.in12k_ft_in1k, license:apache-2.0, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
TimmWrapperForImageClassification
params billions
0.03
context length
12,288
pipeline tag
image-classification
vram gb
2.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
114

Data indexed from public sources. Updated daily.