🧠
Vision Transformer Fine Tune 1 model by kuangbin
⭐ 38.9
🧠
Model

Vision Transformer Fine Tune 1

by kuangbin kuangbin/vision_transformer_fine_tune_1
Free2AITools Nexus Index
38.9 Top 6%
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 3
R: Recency 88
Q: Quality 65
Tech Context
0.3B Params
4.096K Ctx
Vital Performance
27 DL / 30D
Source →

Technical Constraints

Experimental / High Latency
Audited 38.9 FNI Score
Tiny 0.3B Params
4k Context
27 Downloads
8G GPU ~2GB Est. VRAM
Dense VITFORIMAGECLASSIFICATION Architecture
Model Information Summary
Entity Passport
Registry ID kuangbin/vision_transformer_fine_tune_1
Provider huggingface
💾

Compute Threshold

~1.5GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{kuangbin_vision_transformer_fine_tune_1,
  author = {kuangbin},
  title = {Vision Transformer Fine Tune 1 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/kuangbin/vision_transformer_fine_tune_1}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
kuangbin. (2026). Vision Transformer Fine Tune 1 [Model]. Free2AITools. https://huggingface.co/kuangbin/vision_transformer_fine_tune_1

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run vision_transformer_fine_tune_1
🤗 HF Download
huggingface-cli download kuangbin/vision_transformer_fine_tune_1
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Free2AITools Nexus Index V2.0

Methodology Index Protocol
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 3
Recency (R) 88
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Vision Transformer Fine Tune 1: Authority (A:0), Popularity (P:3), Recency (R:88), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
---

🚀 What's Next?

📊

Find Training Datasets

Discover datasets compatible with this model

📈

Compare Benchmarks

See how this model ranks on standard tests

⚡

Deployment Guide

Understand deployment options

Technical Deep Dive

⚠ī¸ 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 →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.
Top Tier

Social Proof

HuggingFace Hub
27Downloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--kuangbin--vision_transformer_fine_tune_1
slug
kuangbin--vision_transformer_fine_tune_1
source
huggingface
author
kuangbin
license
tags
transformers, safetensors, vit, image-classification, arxiv:1910.09700, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
ViTForImageClassification
params billions
0.3
context length
4,096
pipeline tag
image-classification
vram gb
1.5
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
27
stars
0
forks
0

Data indexed from public sources. Updated daily.