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GemmaTestV3 model by elizov
⭐ 37
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Model

GemmaTestV3

by elizov elizov/gemmatestv3
Free2AITools Nexus Index
37.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 19
R: Recency 71
Q: Quality 65
Tech Context
0.27B Params
8.192K Ctx
Vital Performance
457 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 37 FNI Score
Tiny 0.27B Params
8k Context
457 Downloads
8G GPU ~2GB Est. VRAM
Dense GEMMA3FORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID elizov/gemmatestv3
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{elizov_gemmatestv3,
  author = {elizov},
  title = {GemmaTestV3 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/elizov/GemmaTestV3}},
  note = {Accessed via Free2AITools.}
}
APA Style
elizov. (2026). GemmaTestV3 [Model]. Free2AITools. https://huggingface.co/elizov/GemmaTestV3

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gemmatestv3
πŸ€— HF Download
huggingface-cli download elizov/gemmatestv3
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) 19
Recency (R) 71
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for GemmaTestV3: Authority (A:0), Popularity (P:19), Recency (R:71), 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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⚠️ 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
457Downloads
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--elizov--gemmatestv3
slug
elizov--gemmatestv3
source
huggingface
author
elizov
tags
transformers, tensorboard, safetensors, gemma3_text, text-generation, generated_from_trainer, trl, sft, conversational, base_model:google/gemma-3-270m-it, base_model:finetune:google/gemma-3-270m-it, text-generation-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Gemma3ForCausalLM
params billions
0.27
context length
8,192
pipeline tag
text-generation
vram gb
1.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
457
stars
0
forks
0

Data indexed from public sources. Updated daily.