🧠

Model

sdxs

Name: sdxs
Author: recoilme

by recoilme recoilme/sdxs

Free2AITools Nexus Index

39.5

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0

P: Popularity 5

R: Recency 96

Q: Quality 65

Tech Context

1.59 Params

4.096K Ctx

Vital Performance

46 DL / 30D

Source →

Task categories from upstream metadata

🎨AI Art Gen

Technical Constraints

Experimental / High Latency

Low FNI signal 39.5 FNI Score

Tiny 1.59B Params

4k Context

46 Downloads

8G GPU ~3GB Est. VRAM

Restricted OTHER License

Model Information Summary
Entity Passport
Registry ID	recoilme/sdxs
License	Other
Provider	huggingface

💾

Compute Threshold

~2.5GB VRAM

Interactive

Estimate fit

VRAM Estimator (heuristic estimate)

▼

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{recoilme_sdxs,
  author = {recoilme},
  title = {sdxs Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/recoilme/sdxs}},
  note = {Accessed via Free2AITools.}
}

APA Style

recoilme. (2026). sdxs [Model]. Free2AITools. https://huggingface.co/recoilme/sdxs

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run sdxs

🤗 HF Download

huggingface-cli download recoilme/sdxs

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0

Popularity (P) 5

Recency (R) 96

Quality (Q) 65

💬 Index Insight

FNI V2.0 for sdxs: Authority (A:0), Popularity (P:5), Recency (R:96), 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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📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.