🧠
Hypogen T5 Large P model by Marzieh Maleki
⭐ 37.2
🧠
Model

Hypogen T5 Large P

by Marzieh Maleki marzieh-maleki/hypogen-t5-large-p
Free2AITools Nexus Index
37.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 2
R: Recency 99
Q: Quality 45
Tech Context
0.74B Params
512 Ctx
Vital Performance
16 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37.2 FNI Score
Tiny 0.74B Params
1k Context
16 Downloads
8G GPU ~2GB Est. VRAM
Dense T5FORCONDITIONALGENERATION Architecture
Model Information Summary
Entity Passport
Registry ID marzieh-maleki/hypogen-t5-large-p
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.9GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{marzieh_maleki_hypogen_t5_large_p,
  author = {Marzieh Maleki},
  title = {Hypogen T5 Large P Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/marzieh-maleki/hypogen-t5-large-p}},
  note = {Accessed via Free2AITools.}
}
APA Style
Marzieh Maleki. (2026). Hypogen T5 Large P [Model]. Free2AITools. https://huggingface.co/marzieh-maleki/hypogen-t5-large-p

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run hypogen-t5-large-p
πŸ€— HF Download
huggingface-cli download marzieh-maleki/hypogen-t5-large-p
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) 99
Quality (Q) 45

πŸ’¬ Index Insight

FNI V2.0 for Hypogen T5 Large P: Authority (A:0), Popularity (P:2), Recency (R:99), Quality (Q:45). 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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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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
16Downloads
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--marzieh-maleki--hypogen-t5-large-p
slug
marzieh-maleki--hypogen-t5-large-p
source
huggingface
author
Marzieh Maleki
tags
transformers, safetensors, t5, text2text-generation, arxiv:1910.09700, text-generation-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
T5ForConditionalGeneration
params billions
0.74
context length
512
vram gb
1.9
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
16

Data indexed from public sources. Updated daily.