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Qwen3 4b Instruct Reta model by ttttonyhe
⭐ 39
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Model

Qwen3 4b Instruct Reta

by ttttonyhe ttttonyhe/qwen3-4b-instruct-reta
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 22
R: Recency 91
Q: Quality 65
Tech Context
4.02 Params
32.768K Ctx
Vital Performance
600 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
4.02B Params
32k Context
600 Downloads
8G GPU ~6GB Est. VRAM
Dense QWEN3FORCAUSALLM Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID ttttonyhe/qwen3-4b-instruct-reta
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~5.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{ttttonyhe_qwen3_4b_instruct_reta,
  author = {ttttonyhe},
  title = {Qwen3 4b Instruct Reta Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ttttonyhe/Qwen3-4B-Instruct-RETA}},
  note = {Accessed via Free2AITools.}
}
APA Style
ttttonyhe. (2026). Qwen3 4b Instruct Reta [Model]. Free2AITools. https://huggingface.co/ttttonyhe/Qwen3-4B-Instruct-RETA

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3-4b-instruct-reta
πŸ€— HF Download
huggingface-cli download ttttonyhe/qwen3-4b-instruct-reta
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) 22
Recency (R) 91
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3 4b Instruct Reta: Authority (A:0), Popularity (P:22), Recency (R:91), 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.

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.

Social Proof

HuggingFace Hub
600Downloads
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--ttttonyhe--qwen3-4b-instruct-reta
slug
ttttonyhe--qwen3-4b-instruct-reta
source
huggingface
author
ttttonyhe
license
Apache-2.0
tags
transformers, safetensors, qwen3, text-generation, prompt-injection, agent-security, tool-use, agentdojo, trustworthy-ai, conversational, en, arxiv:2606.15441, arxiv:2510.09023, arxiv:2406.13352, arxiv:2211.09527, arxiv:2403.02691, arxiv:2310.12815, arxiv:2509.22830, arxiv:2604.08499, arxiv:2602.05746, arxiv:2510.04885, arxiv:2603.13026, arxiv:2410.02644, base_model:qwen/qwen3-4b-instruct-2507, base_model:finetune:qwen/qwen3-4b-instruct-2507, license:apache-2.0, text-generation-inference, endpoi

βš™οΈ Technical Specs

architecture
Qwen3ForCausalLM
params billions
4.02
context length
32,768
pipeline tag
text-generation
vram gb
5.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
600

Data indexed from public sources. Updated daily.