🧠
Model

Chembed Plug 15

by hsila hsila/chembed-plug-15
Free2AITools Nexus Index
39.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 9
R: Recency 87
Q: Quality 65
Tech Context
0.14B Params
4.096K Ctx
Vital Performance
105 DL / 30D

Technical Constraints

Experimental / High Latency
Low FNI signal 39.9 FNI Score
Tiny 0.14B Params
4k Context
105 Downloads
8G GPU ~2GB Est. VRAM
Dense NOMICBERTMODEL Architecture
Model Information Summary
Entity Passport
Registry ID hsila/chembed-plug-15
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX
@misc{hsila_chembed_plug_15,
  author = {hsila},
  title = {Chembed Plug 15 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/hsila/chembed-plug-15}},
  note = {Accessed via Free2AITools.}
}
APA Style
hsila. (2026). Chembed Plug 15 [Model]. Free2AITools. https://huggingface.co/hsila/chembed-plug-15

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run chembed-plug-15
πŸ€— HF Download
huggingface-cli download hsila/chembed-plug-15
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 9
Recency (R) 87
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Chembed Plug 15: Authority (A:0), Popularity (P:9), Recency (R:87), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

Open data Updated: Live data
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πŸš€ What's Next?

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
105Downloads
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--hsila--chembed-plug-15
slug
hsila--chembed-plug-15
source
huggingface
author
hsila
license
tags
transformers, safetensors, nomic_bert, feature-extraction, custom_code, arxiv:1910.09700, text-embeddings-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
NomicBertModel
params billions
0.14
context length
4,096
pipeline tag
feature-extraction
vram gb
1.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
105
stars
0
forks
0

Data indexed from public sources. Updated daily.