What are the hardware requirements for Gemma 2 2B It Grpo Gsm8k?

Gemma 2 2B It Grpo Gsm8k 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 Grpo Gsm8k and how large is it?

Gemma 2 2B It Grpo Gsm8k is developed by lmassaron, 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 Grpo Gsm8k?

Gemma 2 2B It Grpo Gsm8k 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 Grpo Gsm8k by lmassaron — VRAM 5.2GB, 8K context

Name: Gemma 2 2B It Grpo Gsm8k
Author: lmassaron

Gemma 2 2B It Grpo Gsm8k is an open-source language model by lmassaron. Features: 2b LLM, VRAM: 5.2GB, Context: 8K, LLM Explorer Score: 0.17.

Arxiv:2402.03300 Base model:finetune:google/gem... Base model:google/gemma-2-2b-i... Dataset:openai/gsm8k Endpoints compatible Gemma2 Grpo Region:us Safetensors Sharded Tensorflow Trl

Model Card on HF 🤗: https://huggingface.co/lmassaron/gemma-2-2b-it-grpo-gsm8k

Gemma 2 2B It Grpo Gsm8k Parameters and Internals

LLM Name	Gemma 2 2B It Grpo Gsm8k
Repository 🤗	https://huggingface.co/lmassaron/gemma-2-2b-it-grpo-gsm8k
Base Model(s)	Gemma 2 2B It google/gemma-2-2b-it
Model Size	2b
Required VRAM	5.2 GB
Updated	2026-07-11
Maintainer	lmassaron
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	4.49.0
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Gemma 2 2B It Grpo Gsm8k 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 lmassaron/gemma-2-2b-it-grpo-gsm8k.