What are the hardware requirements for Gemma 2B FT 500 Orca Maths?

Gemma 2B FT 500 Orca Maths requires approximately 5.1 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 2B FT 500 Orca Maths and how large is it?

Gemma 2B FT 500 Orca Maths is developed by anwesh, 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 2B FT 500 Orca Maths?

Gemma 2B FT 500 Orca Maths is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 2B FT 500 Orca Maths by anwesh — VRAM 5.1GB, 8K context

Name: Gemma 2B FT 500 Orca Maths
Author: anwesh

Gemma 2B FT 500 Orca Maths is an open-source language model by anwesh. Features: 2b LLM, VRAM: 5.1GB, Context: 8K, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

4bit Base model:finetune:unsloth/ge... Base model:unsloth/gemma-2b-it... Conversational En Endpoints compatible Gemma Pytorch Quantized Region:us Sft Sharded Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/anwesh/gemma-2B-FT-500-orca-maths

Gemma 2B FT 500 Orca Maths Parameters and Internals

Model Type

text-generation-inference, transformers, unsloth, gemma, trl, sft

Additional Notes

The model utilizes Unsloth techniques to reduce training time and achieve faster fine-tuning, enhancing model performance and efficiency.

Training Details

Methodology:

Finetuned using Huggingface's TRL library and Unsloth to achieve 2x faster training.

LLM Name	Gemma 2B FT 500 Orca Maths
Repository 🤗	https://huggingface.co/anwesh/gemma-2B-FT-500-orca-maths
Base Model(s)	Gemma 2B It Bnb 4bit unsloth/gemma-2b-it-bnb-4bit
Model Size	2b
Required VRAM	5.1 GB
Updated	2026-05-07
Maintainer	anwesh
Model Type	gemma
Model Files	5.0 GB: 1-of-2 0.1 GB: 2-of-2
Supported Languages	en
Quantization Type	4bit
Model Architecture	GemmaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float16

Rank the Gemma 2B FT 500 Orca Maths 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 anwesh/gemma-2B-FT-500-orca-maths.