🧠
Gemma 4 E2b It Agent Posttrain V1.1 model by XcaliburMoon
⭐ 38.5
🧠
Model

Gemma 4 E2b It Agent Posttrain V1.1

by XcaliburMoon xcaliburmoon/gemma-4-e2b-it-agent-posttrain-v1.1
Free2AITools Nexus Index
38.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 8
R: Recency 100
Q: Quality 65
Tech Context
2 Params
4.096K Ctx
Vital Performance
96 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 38.5 FNI Score
Tiny 2B Params
4k Context
96 Downloads
8G GPU ~3GB Est. VRAM
Model Information Summary
Entity Passport
Registry ID xcaliburmoon/gemma-4-e2b-it-agent-posttrain-v1.1
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{xcaliburmoon_gemma_4_e2b_it_agent_posttrain_v1_1,
  author = {XcaliburMoon},
  title = {Gemma 4 E2b It Agent Posttrain V1.1 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/XcaliburMoon/gemma-4-E2B-it-agent-posttrain-v1.1}},
  note = {Accessed via Free2AITools.}
}
APA Style
XcaliburMoon. (2026). Gemma 4 E2b It Agent Posttrain V1.1 [Model]. Free2AITools. https://huggingface.co/XcaliburMoon/gemma-4-E2B-it-agent-posttrain-v1.1

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gemma-4-e2b-it-agent-posttrain-v1.1
πŸ€— HF Download
huggingface-cli download xcaliburmoon/gemma-4-e2b-it-agent-posttrain-v1.1
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) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Gemma 4 E2b It Agent Posttrain V1.1: Authority (A:0), Popularity (P:8), Recency (R:100), 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
96Downloads
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--xcaliburmoon--gemma-4-e2b-it-agent-posttrain-v1.1
slug
xcaliburmoon--gemma-4-e2b-it-agent-posttrain-v1.1
source
huggingface
author
XcaliburMoon
tags
safetensors, gguf, endpoints_compatible, region:us, conversational, transformers, gemma, tool-calling, function-calling, agent, qlora, base_model:google/gemma-4-e2b-it, text-generation, en, base_model:quantized:google/gemma-4-e2b-it

βš™οΈ Technical Specs

params billions
2
context length
4,096
pipeline tag
text-generation
vram gb
2.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
96

Data indexed from public sources. Updated daily.