What are the hardware requirements for Simutrade V1 Clm Rag Gemma3 4B It Adapter?

Simutrade V1 Clm Rag Gemma3 4B It Adapter requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Simutrade V1 Clm Rag Gemma3 4B It Adapter and how large is it?

Simutrade V1 Clm Rag Gemma3 4B It Adapter is developed by simutrade, 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 Simutrade V1 Clm Rag Gemma3 4B It Adapter?

Simutrade V1 Clm Rag Gemma3 4B It Adapter is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Simutrade V1 Clm Rag Gemma3 4B It Adapter by simutrade — VRAM 0.1GB

Name: Simutrade V1 Clm Rag Gemma3 4B It Adapter
Author: simutrade

Simutrade V1 Clm Rag Gemma3 4B It Adapter is an open-source language model by simutrade. Features: 4b LLM, VRAM: 0.1GB, License: gemma, Quantized, Instruction-Based, LLM Explorer Score: 0.27.

4bit Adapter Base model:adapter:unsloth/gem... Base model:unsloth/gemma-3-4b-... Bilingual Conversational Dataset:simutrade/simutrade-ra... En Exports Finetuned Gemma Id Instruct International-trade Logistics Lora Peft Qlora Quantized Rag Region:us Retrieval-augmented-generation Safetensors Sft Unsloth

Model Card on HF 🤗: https://huggingface.co/simutrade/simutrade-v1-clm-rag-gemma3-4b-it-adapter

Simutrade V1 Clm Rag Gemma3 4B It Adapter Parameters and Internals

LLM Name	Simutrade V1 Clm Rag Gemma3 4B It Adapter
Repository 🤗	https://huggingface.co/simutrade/simutrade-v1-clm-rag-gemma3-4b-it-adapter
Base Model(s)	Gemma 3 4B It Bnb 4bit unsloth/gemma-3-4b-it-bnb-4bit
Model Size	4b
Required VRAM	0.1 GB
Updated	2026-08-24
Maintainer	simutrade
Instruction-Based	Yes
Model Files	0.1 GB
Supported Languages	en id
Quantization Type	4bit
Model Architecture	Adapter
License	gemma
Model Max Length	131072
Is Biased	none
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	down_proj\|k_proj\|gate_proj\|v_proj\|up_proj\|o_proj\|q_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16

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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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