🧠
Furniture Use Data Finetuning model by jungwoo3490
⭐ 25.1
🧠
Model

Furniture Use Data Finetuning

by jungwoo3490 hf-model--jungwoo3490--furniture_use_data_finetuning
Nexus Index
25.1 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 1
R: Recency 16
Q: Quality 50
Tech Context
Vital Performance
8 DL / 30D
0.0%
Source →
Audited 25.1 FNI Score
Tiny - Params
- Context
8 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--jungwoo3490--furniture_use_data_finetuning
License Apache-2.0
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__jungwoo3490__furniture_use_data_finetuning,
  author = {jungwoo3490},
  title = {Furniture Use Data Finetuning Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/jungwoo3490/furniture_use_data_finetuning}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
jungwoo3490. (2026). Furniture Use Data Finetuning [Model]. Free2AITools. https://huggingface.co/jungwoo3490/furniture_use_data_finetuning

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download jungwoo3490/furniture_use_data_finetuning
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
25.1
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 1
Recency (R) 16
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Furniture Use Data Finetuning: Semantic (S:50), Authority (A:0), Popularity (P:1), Recency (R:16), Quality (Q:50).

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

furniture_use_data_finetuning

This model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

Training results

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1

⚠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.

Social Proof

HuggingFace Hub
8Downloads
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--jungwoo3490--furniture_use_data_finetuning
slug
jungwoo3490--furniture_use_data_finetuning
source
huggingface
author
jungwoo3490
license
Apache-2.0
tags
transformers, pytorch, detr, object-detection, generated_from_trainer, base_model:facebook/detr-resnet-50, base_model:finetune:facebook/detr-resnet-50, license:apache-2.0, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
object-detection

📊 Engagement & Metrics

downloads
8
stars
0
forks
0

Data indexed from public sources. Updated daily.