🧠
Ror Set Point Retriever Embeddinggemma 300m model by adambuttrick
⭐ 39
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Model

Ror Set Point Retriever Embeddinggemma 300m

by adambuttrick adambuttrick/ror-set-point-retriever-embeddinggemma-300m
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 3
R: Recency 98
Q: Quality 65
Tech Context
0.3B Params
8.192K Ctx
Vital Performance
22 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 0.3B Params
8k Context
22 Downloads
8G GPU ~2GB Est. VRAM
Dense GEMMA3TEXTMODEL Architecture
Restricted GEMMA License
Model Information Summary
Entity Passport
Registry ID adambuttrick/ror-set-point-retriever-embeddinggemma-300m
License Gemma
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{adambuttrick_ror_set_point_retriever_embeddinggemma_300m,
  author = {adambuttrick},
  title = {Ror Set Point Retriever Embeddinggemma 300m Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/adambuttrick/ror-set-point-retriever-embeddinggemma-300m}},
  note = {Accessed via Free2AITools.}
}
APA Style
adambuttrick. (2026). Ror Set Point Retriever Embeddinggemma 300m [Model]. Free2AITools. https://huggingface.co/adambuttrick/ror-set-point-retriever-embeddinggemma-300m

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run ror-set-point-retriever-embeddinggemma-300m
πŸ€— HF Download
huggingface-cli download adambuttrick/ror-set-point-retriever-embeddinggemma-300m
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) 3
Recency (R) 98
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Ror Set Point Retriever Embeddinggemma 300m: Authority (A:0), Popularity (P:3), Recency (R:98), 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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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
22Downloads
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--adambuttrick--ror-set-point-retriever-embeddinggemma-300m
slug
adambuttrick--ror-set-point-retriever-embeddinggemma-300m
source
huggingface
author
adambuttrick
license
Gemma
tags
sentence-transformers, safetensors, gemma3_text, ror, affiliations, entity-linking, retrieval, sentence-similarity, base_model:google/embeddinggemma-300m, base_model:finetune:google/embeddinggemma-300m, license:gemma, text-embeddings-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Gemma3TextModel
params billions
0.3
context length
8,192
pipeline tag
sentence-similarity
vram gb
1.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
22

Data indexed from public sources. Updated daily.