What are the hardware requirements for Gemma 2 2B It Dolly 15K?

Gemma 2 2B It Dolly 15K 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 2 2B It Dolly 15K and how large is it?

Gemma 2 2B It Dolly 15K is developed by kweinmeister, a model with 2b 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 2 2B It Dolly 15K?

Gemma 2 2B It Dolly 15K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 2 2B It Dolly 15K by kweinmeister — VRAM 0.1GB

Name: Gemma 2 2B It Dolly 15K
Author: kweinmeister

Gemma 2 2B It Dolly 15K is an open-source language model by kweinmeister. Features: 2b LLM, VRAM: 0.1GB, License: gemma, LLM Explorer Score: 0.16.

4-bit Adapter Axolotl Base model:adapter:google/gemm... Base model:google/gemma-2-2b-i... Bitsandbytes Conversational Dataset:databricks/databricks-... Finetuned Gemma2 Generated from trainer Lora Peft Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/kweinmeister/gemma-2-2b-it-dolly-15k

Gemma 2 2B It Dolly 15K Parameters and Internals

LLM Name	Gemma 2 2B It Dolly 15K
Repository 🤗	https://huggingface.co/kweinmeister/gemma-2-2b-it-dolly-15k
Base Model(s)	Gemma 2 2B It google/gemma-2-2b-it
Model Size	2b
Required VRAM	0.1 GB
Updated	2026-08-02
Maintainer	kweinmeister
Model Files	0.1 GB 0.1 GB 0.0 GB
Model Architecture	Adapter
License	gemma
Is Biased	none
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	k_proj\|gate_proj\|v_proj\|down_proj\|o_proj\|up_proj\|q_proj
LoRA Alpha	64
LoRA Dropout	0.05
R Param	32

Rank the Gemma 2 2B It Dolly 15K 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 kweinmeister/gemma-2-2b-it-dolly-15k.