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Qwen3.8 2b Sft Fable5 Glint model by ermiaazarkhalili
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Model

Qwen3.8 2b Sft Fable5 Glint

by ermiaazarkhalili ermiaazarkhalili/qwen3.8-2b-sft-fable5-glint
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 2
R: Recency 98
Q: Quality 65
Tech Context
2.27 Params
32.768K Ctx
Vital Performance
19 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 2.27B Params
32k Context
19 Downloads
8G GPU ~5GB Est. VRAM
Dense QWEN3_5FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID ermiaazarkhalili/qwen3.8-2b-sft-fable5-glint
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~4.2GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{ermiaazarkhalili_qwen3_8_2b_sft_fable5_glint,
  author = {ermiaazarkhalili},
  title = {Qwen3.8 2b Sft Fable5 Glint Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ermiaazarkhalili/Qwen3.8-2B-SFT-Fable5-Glint}},
  note = {Accessed via Free2AITools.}
}
APA Style
ermiaazarkhalili. (2026). Qwen3.8 2b Sft Fable5 Glint [Model]. Free2AITools. https://huggingface.co/ermiaazarkhalili/Qwen3.8-2B-SFT-Fable5-Glint

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3.8-2b-sft-fable5-glint
πŸ€— HF Download
huggingface-cli download ermiaazarkhalili/qwen3.8-2b-sft-fable5-glint
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) 2
Recency (R) 98
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3.8 2b Sft Fable5 Glint: Authority (A:0), Popularity (P:2), Recency (R:98), 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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πŸš€ What's Next?

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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.

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
19Downloads
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--ermiaazarkhalili--qwen3.8-2b-sft-fable5-glint
slug
ermiaazarkhalili--qwen3.8-2b-sft-fable5-glint
source
huggingface
author
ermiaazarkhalili
license
Apache-2.0
tags
transformers, safetensors, qwen3_5, image-text-to-text, text-generation-inference, unsloth, conversational, en, base_model:empero-ai/qwen3.8-2b-distill, base_model:finetune:empero-ai/qwen3.8-2b-distill, license:apache-2.0, endpoints_compatible, region:us, lora, trl, sft, text-generation, base_model:adapter:empero-ai/qwen3.8-2b-distill

βš™οΈ Technical Specs

architecture
Qwen3_5ForConditionalGeneration
params billions
2.27
context length
32,768
pipeline tag
text-generation
vram gb
4.2
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
19

Data indexed from public sources. Updated daily.