🧠
Gemma Sea Lion V4 27b It model by aisingapore
⭐ 55.7
🧠
Model

Gemma Sea Lion V4 27b It

by aisingapore aisingapore/gemma-sea-lion-v4-27b-it
Free2AITools Nexus Index
55.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 48
P: Popularity 31
R: Recency 99
Q: Quality 65
Tech Context
27.43 Params
8.192K Ctx
Vital Performance
1.9K DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue
Low FNI signal 55.7 FNI Score
27.43B Params
8k Context
1.9K Downloads
24G GPU ~22GB Est. VRAM
Dense GEMMA3FORCONDITIONALGENERATION Architecture
Restricted GEMMA License
Model Information Summary
Entity Passport
Registry ID aisingapore/gemma-sea-lion-v4-27b-it
License Gemma
Provider huggingface
πŸ’Ύ

Compute Threshold

~21.9GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{aisingapore_gemma_sea_lion_v4_27b_it,
  author = {aisingapore},
  title = {Gemma Sea Lion V4 27b It Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/aisingapore/Gemma-SEA-LION-v4-27B-IT}},
  note = {Accessed via Free2AITools.}
}
APA Style
aisingapore. (2026). Gemma Sea Lion V4 27b It [Model]. Free2AITools. https://huggingface.co/aisingapore/Gemma-SEA-LION-v4-27B-IT

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gemma-sea-lion-v4-27b-it
πŸ€— HF Download
huggingface-cli download aisingapore/gemma-sea-lion-v4-27b-it
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) 48
Popularity (P) 31
Recency (R) 99
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Gemma Sea Lion V4 27b It: Authority (A:48), Popularity (P:31), Recency (R:99), 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
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

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.

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.

Social Proof

HuggingFace Hub
1.9KDownloads
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--aisingapore--gemma-sea-lion-v4-27b-it
slug
aisingapore--gemma-sea-lion-v4-27b-it
source
huggingface
author
aisingapore
license
Gemma
tags
transformers, safetensors, gemma3, image-text-to-text, text-generation, conversational, en, zh, vi, id, th, fil, ta, ms, km, lo, my, jv, su, arxiv:2502.14301, arxiv:2311.07911, arxiv:2306.05685, arxiv:1910.09700, base_model:aisingapore/gemma-sea-lion-v4-27b, license:gemma, text-generation-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Gemma3ForConditionalGeneration
params billions
27.43
context length
8,192
pipeline tag
text-generation
vram gb
21.9
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
1,915
stars
null
forks
null

Data indexed from public sources. Updated daily.