🧠
Vit Base Oxford Iiit Pets model by ISxOdin
⭐ 39.7
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Model

Vit Base Oxford Iiit Pets

by ISxOdin isxodin/vit-base-oxford-iiit-pets
Free2AITools Nexus Index
39.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 33
P: Popularity 61
R: Recency 37
Q: Quality 65
Tech Context
0.09B Params
4.096K Ctx
Vital Performance
171.1K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.7 FNI Score
Tiny 0.09B Params
4k Context
Hot 171.1K Downloads
8G GPU ~2GB Est. VRAM
Dense VITFORIMAGECLASSIFICATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID isxodin/vit-base-oxford-iiit-pets
License Apache-2.0
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{isxodin_vit_base_oxford_iiit_pets,
  author = {ISxOdin},
  title = {Vit Base Oxford Iiit Pets Model},
  year = {2025},
  howpublished = {\url{https://huggingface.co/ISxOdin/vit-base-oxford-iiit-pets}},
  note = {Accessed via Free2AITools.}
}
APA Style
ISxOdin. (2025). Vit Base Oxford Iiit Pets [Model]. Free2AITools. https://huggingface.co/ISxOdin/vit-base-oxford-iiit-pets

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run vit-base-oxford-iiit-pets
πŸ€— HF Download
huggingface-cli download isxodin/vit-base-oxford-iiit-pets
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) 33
Popularity (P) 61
Recency (R) 37
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Vit Base Oxford Iiit Pets: Authority (A:33), Popularity (P:61), Recency (R:37), 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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πŸš€ What's Next?

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Deployment reference

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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
171.1KDownloads
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--isxodin--vit-base-oxford-iiit-pets
slug
isxodin--vit-base-oxford-iiit-pets
source
huggingface
author
ISxOdin
license
Apache-2.0
tags
transformers, tensorboard, safetensors, vit, image-classification, generated_from_trainer, zero-shot-image-classification, base_model:google/vit-base-patch16-224, base_model:finetune:google/vit-base-patch16-224, license:apache-2.0, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
ViTForImageClassification
params billions
0.09
context length
4,096
pipeline tag
image-classification
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
171,063
stars
0
forks
0

Data indexed from public sources. Updated daily.