What are the hardware requirements for Gemma 3 4B It Triplet Extractor?

Gemma 3 4B It Triplet Extractor requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 3 4B It Triplet Extractor and how large is it?

Gemma 3 4B It Triplet Extractor is developed by dams2005, a model with 4b 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 Gemma 3 4B It Triplet Extractor?

Gemma 3 4B It Triplet Extractor is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 3 4B It Triplet Extractor by dams2005 — VRAM 0.1GB

Name: Gemma 3 4B It Triplet Extractor
Author: dams2005

Gemma 3 4B It Triplet Extractor is an open-source language model by dams2005. Features: 4b LLM, VRAM: 0.1GB, License: gemma, LLM Explorer Score: 0.23.

Base model:adapter:google/gemm... Base model:google/gemma-3-4b-i... Conversational Gemma-3 Information-extraction Json Knowledge-graph Lora Peft Region:us Relation-extraction Safetensors Triplet-extraction

Model Card on HF 🤗: https://huggingface.co/dams2005/gemma-3-4b-it-triplet-extractor

Gemma 3 4B It Triplet Extractor Parameters and Internals

LLM Name	Gemma 3 4B It Triplet Extractor
Repository 🤗	https://huggingface.co/dams2005/gemma-3-4b-it-triplet-extractor
Base Model(s)	Gemma 3 4B It google/gemma-3-4b-it
Model Size	4b
Required VRAM	0.1 GB
Updated	2026-10-04
Maintainer	dams2005
Model Files	0.1 GB 0.0 GB
Model Architecture	AutoModel
License	gemma
Is Biased	none
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	gate_proj\|up_proj\|q_proj\|k_proj\|v_proj\|o_proj\|down_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16

Rank the Gemma 3 4B It Triplet Extractor 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

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Note: green Score (e.g. "73.2") means that the model is better than dams2005/gemma-3-4b-it-triplet-extractor.