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Gemma3 12b Deedexp model by anandkaman
⭐ 39
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Model

Gemma3 12b Deedexp

by anandkaman anandkaman/gemma3_12b_deedexp
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 17
R: Recency 97
Q: Quality 65
Tech Context
12.19 Params
8.192K Ctx
Vital Performance
342 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
12.19B Params
8k Context
342 Downloads
24G GPU ~11GB Est. VRAM
Dense GEMMA3FORCONDITIONALGENERATION Architecture
Restricted GEMMA License
Model Information Summary
Entity Passport
Registry ID anandkaman/gemma3_12b_deedexp
License Gemma
Provider huggingface
πŸ’Ύ

Compute Threshold

~10.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{anandkaman_gemma3_12b_deedexp,
  author = {anandkaman},
  title = {Gemma3 12b Deedexp Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/anandkaman/gemma3_12b_deedexp}},
  note = {Accessed via Free2AITools.}
}
APA Style
anandkaman. (2026). Gemma3 12b Deedexp [Model]. Free2AITools. https://huggingface.co/anandkaman/gemma3_12b_deedexp

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gemma3_12b_deedexp
πŸ€— HF Download
huggingface-cli download anandkaman/gemma3_12b_deedexp
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) 17
Recency (R) 97
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Gemma3 12b Deedexp: Authority (A:0), Popularity (P:17), Recency (R:97), 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.

Social Proof

HuggingFace Hub
342Downloads
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--anandkaman--gemma3_12b_deedexp
slug
anandkaman--gemma3_12b_deedexp
source
huggingface
author
anandkaman
license
Gemma
tags
transformers, safetensors, gemma3, image-text-to-text, information-extraction, kannada, legal-documents, json, text-generation, conversational, kn, en, base_model:google/gemma-3-12b-it, base_model:finetune:google/gemma-3-12b-it, license:gemma, text-generation-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Gemma3ForConditionalGeneration
params billions
12.19
context length
8,192
pipeline tag
text-generation
vram gb
10.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
342

Data indexed from public sources. Updated daily.