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Gemma3 1b Cpt model by Efe2898
⭐ 29.2
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Model

Gemma3 1b Cpt

by Efe2898 efe2898/gemma3-1b-cpt
Free2AITools Nexus Index
29.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 70
Q: Quality 50
Tech Context
1 Params
8.192K Ctx
Vital Performance —
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 29.2 FNI Score
Tiny 1B Params
8k Context
0 Downloads
8G GPU ~2GB Est. VRAM
Dense GEMMA3FORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID efe2898/gemma3-1b-cpt
Provider huggingface
πŸ’Ύ

Compute Threshold

~2GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{efe2898_gemma3_1b_cpt,
  author = {Efe2898},
  title = {Gemma3 1b Cpt Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Efe2898/gemma3-1b-cpt}},
  note = {Accessed via Free2AITools.}
}
APA Style
Efe2898. (2026). Gemma3 1b Cpt [Model]. Free2AITools. https://huggingface.co/Efe2898/gemma3-1b-cpt

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gemma3-1b-cpt
πŸ€— HF Download
huggingface-cli download efe2898/gemma3-1b-cpt
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) 0
Recency (R) 70
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Gemma3 1b Cpt: Authority (A:0), Popularity (P:0), Recency (R:70), Quality (Q:50). 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.

View Original Source β†’

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.
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--efe2898--gemma3-1b-cpt
slug
efe2898--gemma3-1b-cpt
source
huggingface
author
Efe2898
tags
transformers, safetensors, gemma3_text, text-generation, conversational, arxiv:1910.09700, text-generation-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Gemma3ForCausalLM
params billions
1
context length
8,192
pipeline tag
text-generation
vram gb
2
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
0
stars
0
forks
0

Data indexed from public sources. Updated daily.