What are the hardware requirements for Gemma 2 2B It Finetuned 1 Def?

Gemma 2 2B It Finetuned 1 Def requires approximately 5.2 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 2 2B It Finetuned 1 Def and how large is it?

Gemma 2 2B It Finetuned 1 Def is developed by xw17, 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 Finetuned 1 Def?

Gemma 2 2B It Finetuned 1 Def 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 Finetuned 1 Def by xw17 — VRAM 5.2GB, 8K context

Name: Gemma 2 2B It Finetuned 1 Def
Author: xw17

Gemma 2 2B It Finetuned 1 Def is an open-source language model by xw17. Features: 2b LLM, VRAM: 5.2GB, Context: 8K, Fine-Tuned, LLM Explorer Score: 0.17.

Arxiv:1910.09700 Conversational Endpoints compatible Finetuned Gemma2 Region:us Safetensors Sft Sharded Tensorflow Trl

Model Card on HF 🤗: https://huggingface.co/xw17/gemma-2-2b-it_finetuned_1_def

Gemma 2 2B It Finetuned 1 Def Parameters and Internals

LLM Name	Gemma 2 2B It Finetuned 1 Def
Repository 🤗	https://huggingface.co/xw17/gemma-2-2b-it_finetuned_1_def
Model Size	2b
Required VRAM	5.2 GB
Updated	2026-08-07
Maintainer	xw17
Model Type	gemma2
Model Files	5.0 GB: 1-of-2 0.2 GB: 2-of-2
Model Architecture	Gemma2ForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.47.0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Gemma 2 2B It Finetuned 1 Def capabilities

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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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Note: green Score (e.g. "73.2") means that the model is better than xw17/gemma-2-2b-it_finetuned_1_def.