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Gpt2 Turkish Configc 20k model by aariciah
⭐ 39.4
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Model

Gpt2 Turkish Configc 20k

by aariciah aariciah/gpt2-turkish-configc-20k
Free2AITools Nexus Index
39.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 8
R: Recency 76
Q: Quality 65
Tech Context
0.1B Params
1.024K Ctx
Vital Performance
100 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 39.4 FNI Score
Tiny 0.1B Params
1k Context
100 Downloads
8G GPU ~2GB Est. VRAM
Dense GPT2LMHEADMODEL Architecture
Model Information Summary
Entity Passport
Registry ID aariciah/gpt2-turkish-configc-20k
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{aariciah_gpt2_turkish_configc_20k,
  author = {aariciah},
  title = {Gpt2 Turkish Configc 20k Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/aariciah/gpt2-turkish-configC-20k}},
  note = {Accessed via Free2AITools.}
}
APA Style
aariciah. (2026). Gpt2 Turkish Configc 20k [Model]. Free2AITools. https://huggingface.co/aariciah/gpt2-turkish-configC-20k

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gpt2-turkish-configc-20k
πŸ€— HF Download
huggingface-cli download aariciah/gpt2-turkish-configc-20k
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 8
Recency (R) 76
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Gpt2 Turkish Configc 20k: Authority (A:0), Popularity (P:8), Recency (R:76), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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Technical Deep Dive

⚠️ 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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πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ 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
100Downloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--aariciah--gpt2-turkish-configc-20k
slug
aariciah--gpt2-turkish-configc-20k
source
huggingface
author
aariciah
tags
transformers, safetensors, gpt2, text-generation, generated_from_trainer, text-generation-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
GPT2LMHeadModel
params billions
0.1
context length
1,024
pipeline tag
text-generation
vram gb
1.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
100

Data indexed from public sources. Updated daily.