🧠
Myawesomemodel Testrepo model by mcptester
⭐ 29.4
🧠
Model

Myawesomemodel Testrepo

by mcptester mcptester/myawesomemodel-testrepo
Free2AITools Nexus Index
29.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 4
R: Recency 69
Q: Quality 50
Tech Context
512 Ctx
Vital Performance
39 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 29.4 FNI Score
Tiny - Params
1k Context
39 Downloads
Dense BERTMODEL Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID mcptester/myawesomemodel-testrepo
License MIT
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{mcptester_myawesomemodel_testrepo,
  author = {mcptester},
  title = {Myawesomemodel Testrepo Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/mcptester/MyAwesomeModel-TestRepo}},
  note = {Accessed via Free2AITools.}
}
APA Style
mcptester. (2026). Myawesomemodel Testrepo [Model]. Free2AITools. https://huggingface.co/mcptester/MyAwesomeModel-TestRepo

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download mcptester/myawesomemodel-testrepo
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) 4
Recency (R) 69
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Myawesomemodel Testrepo: Authority (A:0), Popularity (P:4), Recency (R:69), Quality (Q:50). 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.

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
39Downloads
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--mcptester--myawesomemodel-testrepo
slug
mcptester--myawesomemodel-testrepo
source
huggingface
author
mcptester
license
MIT
tags
transformers, pytorch, bert, feature-extraction, license:mit, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
BertModel
context length
512
pipeline tag
feature-extraction

πŸ“Š Engagement & Metrics

downloads
39
stars
0
forks
0

Data indexed from public sources. Updated daily.