🧠
Calculator Model Test model by Gi8on
⭐ 37
🧠
Model

Calculator Model Test

by Gi8on hf-model--gi8on--calculator_model_test
Free2AITools Nexus Index
37.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 3
R: Recency 96
Q: Quality 45
Tech Context
0.01B Params
4.096K Ctx
Vital Performance
26 DL / 30D
0.0%
Source →
Audited 37 FNI Score
Tiny 0.01B Params
4k Context
26 Downloads
8G GPU ~2GB Est. VRAM
Dense ENCODERDECODERMODEL Architecture
Model Information Summary
Entity Passport
Registry ID hf-model--gi8on--calculator_model_test
Provider huggingface
💾

Compute Threshold

~1.3GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__gi8on__calculator_model_test,
  author = {Gi8on},
  title = {Calculator Model Test Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Gi8on/calculator_model_test}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Gi8on. (2026). Calculator Model Test [Model]. Free2AITools. https://huggingface.co/Gi8on/calculator_model_test

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run calculator_model_test
🤗 HF Download
huggingface-cli download gi8on/calculator_model_test
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Free2AITools Nexus Index V2.0

Methodology Index Protocol
Semantic (S) 50
Authority (A) 0
Popularity (P) 3
Recency (R) 96
Quality (Q) 45

đŸ’Ŧ Index Insight

FNI V2.0 for Calculator Model Test: Semantic (S:50), Authority (A:0), Popularity (P:3), Recency (R:96), Quality (Q:45).

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

calculator_model_test

This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6463

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: 0.001
  • train_batch_size: 512
  • eval_batch_size: 512
  • 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
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss
3.4635 1.0 5 2.8650
2.5314 2.0 10 2.1158
1.9819 3.0 15 1.8063
1.6986 4.0 20 1.6031
1.5730 5.0 25 1.5538
1.5102 6.0 30 1.5036
1.4481 7.0 35 1.4591
1.3779 8.0 40 1.3530
1.3051 9.0 45 1.2608
1.2610 10.0 50 1.1978
1.2074 11.0 55 1.2343
1.1567 12.0 60 1.1180
1.1375 13.0 65 1.1520
1.1428 14.0 70 1.1030
1.0972 15.0 75 1.0581
1.0503 16.0 80 0.9979
0.9758 17.0 85 0.9513
0.9473 18.0 90 0.9317
0.9206 19.0 95 0.9380
0.9384 20.0 100 0.8643
0.8769 21.0 105 0.9630
0.9673 22.0 110 0.9533
0.9098 23.0 115 0.8435
0.8675 24.0 120 0.8262
0.8382 25.0 125 0.8295
0.8148 26.0 130 0.7936
0.8002 27.0 135 0.7727
0.7794 28.0 140 0.7617
0.7631 29.0 145 0.7373
0.7419 30.0 150 0.7182
0.7297 31.0 155 0.7168
0.7208 32.0 160 0.6962
0.7054 33.0 165 0.6853
0.6964 34.0 170 0.6826
0.6895 35.0 175 0.6700
0.6787 36.0 180 0.6599
0.6689 37.0 185 0.6539
0.6651 38.0 190 0.6495
0.6646 39.0 195 0.6490
0.6592 40.0 200 0.6463

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

⚠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
26Downloads
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--gi8on--calculator_model_test
slug
gi8on--calculator_model_test
source
huggingface
author
Gi8on
license
tags
transformers, safetensors, encoder-decoder, text2text-generation, generated_from_trainer, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
EncoderDecoderModel
params billions
0.01
context length
4,096
pipeline tag
vram gb
1.3
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
26
stars
0
forks
0

Data indexed from public sources. Updated daily.