🧠
Ane Extraction Qwen3.5 2b model by Ekwav
⭐ 31.5
🧠
Model

Ane Extraction Qwen3.5 2b

by Ekwav ekwav/ane-extraction-qwen3.5-2b
Free2AITools Nexus Index
31.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 1
R: Recency 68
Q: Quality 65
Tech Context
2.27 Params
32.768K Ctx
Vital Performance
12 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 31.5 FNI Score
Tiny 2.27B Params
32k Context
12 Downloads
8G GPU ~5GB Est. VRAM
Dense QWEN3_5FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID ekwav/ane-extraction-qwen3.5-2b
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{ekwav_ane_extraction_qwen3_5_2b,
  author = {Ekwav},
  title = {Ane Extraction Qwen3.5 2b Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Ekwav/ane-extraction-qwen3.5-2b}},
  note = {Accessed via Free2AITools.}
}
APA Style
Ekwav. (2026). Ane Extraction Qwen3.5 2b [Model]. Free2AITools. https://huggingface.co/Ekwav/ane-extraction-qwen3.5-2b

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run ane-extraction-qwen3.5-2b
πŸ€— HF Download
huggingface-cli download ekwav/ane-extraction-qwen3.5-2b

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) 1
Recency (R) 68
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Ane Extraction Qwen3.5 2b: Authority (A:0), Popularity (P:1), Recency (R:68), 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.

Social Proof

HuggingFace Hub
12Downloads
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--ekwav--ane-extraction-qwen3.5-2b
slug
ekwav--ane-extraction-qwen3.5-2b
source
huggingface
author
Ekwav
license
Apache-2.0
tags
safetensors, qwen3_5, extraction, marketplace, kleinanzeigen, qwen3, lora, ane, text-generation, conversational, de, en, base_model:unsloth/qwen3.5-2b, base_model:adapter:unsloth/qwen3.5-2b, license:apache-2.0, region:us

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
12
stars
0
forks
0

Data indexed from public sources. Updated daily.