🧠
Foodextract Gemma 3 270m Fine Tune V1 model by mrdbourke
⭐ 37.7
🧠
Model

Foodextract Gemma 3 270m Fine Tune V1

by mrdbourke mrdbourke/foodextract-gemma-3-270m-fine-tune-v1
Free2AITools Nexus Index
37.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 24
R: Recency 74
Q: Quality 65
Tech Context
0.27B Params
8.192K Ctx
Vital Performance
755 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 37.7 FNI Score
Tiny 0.27B Params
8k Context
755 Downloads
8G GPU ~2GB Est. VRAM
Dense GEMMA3FORCAUSALLM Architecture
Restricted GEMMA License
Model Information Summary
Entity Passport
Registry ID mrdbourke/foodextract-gemma-3-270m-fine-tune-v1
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{mrdbourke_foodextract_gemma_3_270m_fine_tune_v1,
  author = {mrdbourke},
  title = {Foodextract Gemma 3 270m Fine Tune V1 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/mrdbourke/FoodExtract-gemma-3-270m-fine-tune-v1}},
  note = {Accessed via Free2AITools.}
}
APA Style
mrdbourke. (2026). Foodextract Gemma 3 270m Fine Tune V1 [Model]. Free2AITools. https://huggingface.co/mrdbourke/FoodExtract-gemma-3-270m-fine-tune-v1

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run foodextract-gemma-3-270m-fine-tune-v1
πŸ€— HF Download
huggingface-cli download mrdbourke/foodextract-gemma-3-270m-fine-tune-v1
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) 29
Popularity (P) 24
Recency (R) 74
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Foodextract Gemma 3 270m Fine Tune V1: Authority (A:29), Popularity (P:24), Recency (R:74), 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
755Downloads
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--mrdbourke--foodextract-gemma-3-270m-fine-tune-v1
slug
mrdbourke--foodextract-gemma-3-270m-fine-tune-v1
source
huggingface
author
mrdbourke
license
Gemma
tags
transformers, safetensors, gemma3_text, text-generation, generated_from_trainer, sft, trl, conversational, base_model:google/gemma-3-270m-it, base_model:finetune:google/gemma-3-270m-it, license:gemma, text-generation-inference, endpoints_compatible, region:us, arxiv:2506.14111

βš™οΈ Technical Specs

architecture
Gemma3ForCausalLM
params billions
0.27
context length
8,192
pipeline tag
text-generation
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
755
stars
0
forks
0

Data indexed from public sources. Updated daily.