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Model

Food101 Vit Dinov3

Name: Food101 Vit Dinov3
Author: merve

by merve hf-model--merve--food101-vit-dinov3

Free2AITools Nexus Index

39.1 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 17

R: Recency 90

Q: Quality 65

Tech Context

0.09B Params

4.096K Ctx

Vital Performance

358 DL / 30D

0.0%

Source →

Audited 39.1 FNI Score

Tiny 0.09B Params

4k Context

358 Downloads

8G GPU ~2GB Est. VRAM

Dense TIMMWRAPPERFORIMAGECLASSIFICATION Architecture

Restricted OTHER License

Model Information Summary
Entity Passport
Registry ID	hf-model--merve--food101-vit-dinov3
License	Other
Provider	huggingface

💾

Compute Threshold

~1.4GB VRAM

Interactive

Analyze Hardware

Hardware Compatibility Test

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* Static estimation for 4-Bit Quantization.

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Cite this model

Academic & Research Attribution

BibTeX

@misc{hf_model__merve__food101_vit_dinov3,
  author = {merve},
  title = {Food101 Vit Dinov3 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/merve/food101-vit-dinov3}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

merve. (2026). Food101 Vit Dinov3 [Model]. Free2AITools. https://huggingface.co/merve/food101-vit-dinov3

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run food101-vit-dinov3

🤗 HF Download

huggingface-cli download merve/food101-vit-dinov3

📦 Install Lib

pip install -U transformers

⚖️ Free2AITools Nexus Index V2.0

Methodology Index Protocol

Semantic (S) 50

Authority (A) 0

Popularity (P) 17

Recency (R) 90

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Food101 Vit Dinov3: Semantic (S:50), Authority (A:0), Popularity (P:17), Recency (R:90), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

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🚀 What's Next?

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Deployment Guide

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Technical Deep Dive

food101-vit-dinov3

This model is a fine-tuned version of timm/vit_base_patch16_dinov3.lvd1689m on the ethz/food101 dataset. It achieves the following results on the evaluation set:

Loss: 0.0491
Accuracy: 0.9865

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 10.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7454	1.0	237	0.2419	0.9493
0.3067	2.0	474	0.1198	0.9671
0.2526	3.0	711	0.0859	0.9747
0.1810	4.0	948	0.0706	0.9802
0.1365	5.0	1185	0.0621	0.9802
0.1284	6.0	1422	0.0648	0.9814
0.1034	7.0	1659	0.0523	0.9830
0.0815	8.0	1896	0.0566	0.9834
0.0810	9.0	2133	0.0503	0.9861
0.0597	10.0	2370	0.0491	0.9865

Framework versions

Transformers 5.3.0.dev0
Pytorch 2.10.0+cu128
Datasets 4.6.1
Tokenizers 0.22.2

⚠️ 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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📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• 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

358Downloads

Hub Discussions

🤗 Data Source: Hugging Face ↗

🔄 Daily sync (03:00 UTC)

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

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--merve--food101-vit-dinov3
slug: merve--food101-vit-dinov3
source: huggingface
author: merve
license: Other
tags: transformers, safetensors, timm_wrapper, image-classification, vision, timm, generated_from_trainer, base_model:timm/vit_base_patch16_dinov3.lvd1689m, license:other, endpoints_compatible, region:us

⚙️ Technical Specs

architecture: TimmWrapperForImageClassification
params billions: 0.09
context length: 4,096
pipeline tag: image-classification
vram gb: 1.4
vram is estimated: true
vram formula: VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads: 358
stars: 0
forks: null

Data indexed from public sources. Updated daily.