🧠
Vit Base Patch16 224 In21k Landscape Recognition model by DunnBC22
⭐ 37.5
🧠
Model

Vit Base Patch16 224 In21k Landscape Recognition

by DunnBC22 dunnbc22/vit-base-patch16-224-in21k-landscape_recognition
Free2AITools Nexus Index
37.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 4
R: Recency 87
Q: Quality 50
Tech Context
21.504K Ctx
Vital Performance
37 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37.5 FNI Score
Tiny - Params
21k Context
37 Downloads
Dense VITFORIMAGECLASSIFICATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID dunnbc22/vit-base-patch16-224-in21k-landscape_recognition
License Apache-2.0
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{dunnbc22_vit_base_patch16_224_in21k_landscape_recognition,
  author = {DunnBC22},
  title = {Vit Base Patch16 224 In21k Landscape Recognition Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k-Landscape_Recognition}},
  note = {Accessed via Free2AITools.}
}
APA Style
DunnBC22. (2026). Vit Base Patch16 224 In21k Landscape Recognition [Model]. Free2AITools. https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k-Landscape_Recognition

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download dunnbc22/vit-base-patch16-224-in21k-landscape_recognition
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) 29
Popularity (P) 4
Recency (R) 87
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Vit Base Patch16 224 In21k Landscape Recognition: Authority (A:29), Popularity (P:4), Recency (R:87), 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
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

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
37Downloads
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--dunnbc22--vit-base-patch16-224-in21k-landscape_recognition
slug
dunnbc22--vit-base-patch16-224-in21k-landscape_recognition
source
huggingface
author
DunnBC22
license
Apache-2.0
tags
transformers, pytorch, tensorboard, vit, image-classification, generated_from_trainer, landscape, en, license:apache-2.0, model-index, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
ViTForImageClassification
params billions
null
context length
21,504
pipeline tag
image-classification

πŸ“Š Engagement & Metrics

downloads
37
stars
0
forks
0

Data indexed from public sources. Updated daily.