What are the hardware requirements for FoodExtract Gemma 3 270M Finetuned?

FoodExtract Gemma 3 270M Finetuned requires approximately 1.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed FoodExtract Gemma 3 270M Finetuned and how large is it?

FoodExtract Gemma 3 270M Finetuned is developed by xorslider, a model with 270m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate FoodExtract Gemma 3 270M Finetuned?

FoodExtract Gemma 3 270M Finetuned is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

FoodExtract Gemma 3 270M Finetuned by xorslider — VRAM 1.1GB, 32K context

Name: FoodExtract Gemma 3 270M Finetuned
Author: xorslider

FoodExtract Gemma 3 270M Finetuned is an open-source language model by xorslider. Features: 270m LLM, VRAM: 1.1GB, Context: 32K, License: gemma, Fine-Tuned, LLM Explorer Score: 0.31.

Base model:finetune:google/gem... Base model:google/gemma-3-270m... Conversational Endpoints compatible Finetuned Food-extraction Gemma3 text Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/xorslider/FoodExtract-gemma-3-270m-finetuned

FoodExtract Gemma 3 270M Finetuned Parameters and Internals

LLM Name	FoodExtract Gemma 3 270M Finetuned
Repository 🤗	https://huggingface.co/xorslider/FoodExtract-gemma-3-270m-finetuned
Base Model(s)	Gemma 3 270M It google/gemma-3-270m-it
Model Size	270m
Required VRAM	1.1 GB
Updated	2026-10-19
Maintainer	xorslider
Model Type	gemma3_text
Model Files	1.1 GB 0.0 GB
Model Architecture	Gemma3ForCausalLM
License	gemma
Context Length	32768
Model Max Length	32768
Transformers Version	5.16.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	262144

Rank the FoodExtract Gemma 3 270M Finetuned capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to FoodExtract Gemma 3 270M Finetuned

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 3 270M	32K / 0.5 GB	5434146	1041
Gemma 3 270M It	32K / 0.5 GB	1222057	604
Functiongemma 270M It	32K / 0.5 GB	38635	1044
Kavach PII 270M	32K / 0.5 GB	533	1
Gemma 3 270M	32K / 0.5 GB	234	0
...ract Gemma 3 270M Fine Tune V1	32K / 0.5 GB	153	1
...gemma 270M It Prepaid Cards V2	32K / 0.5 GB	534	0
Gemma3 270M Manumit V1	32K / 0.5 GB	134	0
Functiongemma 270M It	32K / 0.5 GB	4949	13
Gemma 3 270M It	32K / 0.5 GB	21566	23

Note: green Score (e.g. "73.2") means that the model is better than xorslider/FoodExtract-gemma-3-270m-finetuned.