🧠
Ateso Model V2 Auto model by stockley
⭐ 40.7
🧠
Model

Ateso Model V2 Auto

by stockley hf-model--stockley--ateso-model-v2-auto
Nexus Index
40.7 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 18
R: Recency 93
Q: Quality 65
Tech Context
Vital Performance
390 DL / 30D
0.0%
Source →
Audited 40.7 FNI Score
Tiny - Params
- Context
390 Downloads
Model Information Summary
Entity Passport
Registry ID hf-model--stockley--ateso-model-v2-auto
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__stockley__ateso_model_v2_auto,
  author = {stockley},
  title = {Ateso Model V2 Auto Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/stockley/ateso-model-v2-auto}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
stockley. (2026). Ateso Model V2 Auto [Model]. Free2AITools. https://huggingface.co/stockley/ateso-model-v2-auto

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download stockley/ateso-model-v2-auto
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
40.7
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 18
Recency (R) 93
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Ateso Model V2 Auto: Semantic (S:50), Authority (A:0), Popularity (P:18), Recency (R:93), 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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Deployment Guide

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Technical Deep Dive

ateso-model-v2-auto

This model is a fine-tuned version of 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: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 8
  • 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: 20

Training results

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
390Downloads
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--stockley--ateso-model-v2-auto
slug
stockley--ateso-model-v2-auto
source
huggingface
author
stockley
license
tags
transformers, safetensors, roberta, fill-mask, generated_from_trainer, endpoints_compatible, region:us, xlm-roberta

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
fill-mask

📊 Engagement & Metrics

downloads
390
stars
0
forks
0

Data indexed from public sources. Updated daily.