🧠
Humaneyes model by Eemansleepdeprived
⭐ 32.1
🧠
Model

Humaneyes

by Eemansleepdeprived eemansleepdeprived/humaneyes
Free2AITools Nexus Index
32.1
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 46
P: Popularity 19
R: Recency 27
Q: Quality 65
Tech Context
0.57B Params
1.024K Ctx
Vital Performance
435 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 32.1 FNI Score
Tiny 0.57B Params
1k Context
435 Downloads
8G GPU ~2GB Est. VRAM
Dense PEGASUSFORCONDITIONALGENERATION Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID eemansleepdeprived/humaneyes
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.7GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{eemansleepdeprived_humaneyes,
  author = {Eemansleepdeprived},
  title = {Humaneyes Model},
  year = {2024},
  howpublished = {\url{https://huggingface.co/Eemansleepdeprived/Humaneyes}},
  note = {Accessed via Free2AITools.}
}
APA Style
Eemansleepdeprived. (2024). Humaneyes [Model]. Free2AITools. https://huggingface.co/Eemansleepdeprived/Humaneyes

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run humaneyes
πŸ€— HF Download
huggingface-cli download eemansleepdeprived/humaneyes
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) 46
Popularity (P) 19
Recency (R) 27
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Humaneyes: Authority (A:46), Popularity (P:19), Recency (R:27), 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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Deployment reference

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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
435Downloads
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--eemansleepdeprived--humaneyes
slug
eemansleepdeprived--humaneyes
source
huggingface
author
Eemansleepdeprived
license
MIT
tags
transformers, safetensors, pegasus, text2text-generation, hunmaniser, ai, aidetection, text-generation, paraphrasing, nlp, en, base_model:tuner007/pegasus_paraphrase, base_model:finetune:tuner007/pegasus_paraphrase, license:mit, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
PegasusForConditionalGeneration
params billions
0.57
context length
1,024
pipeline tag
text-generation
vram gb
1.7
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
435
stars
0
forks
0

Data indexed from public sources. Updated daily.