What are the hardware requirements for Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium?

Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium requires approximately 2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium and how large is it?

Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium is developed by erayalp, a model with 0.5b 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 Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium?

Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium by erayalp — VRAM 2GB, 32K context

Name: Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium
Author: erayalp

Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium is an open-source language model by erayalp. Features: 0.5b LLM, VRAM: 2GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.18.

Base model:erayalp/qwen2.5-0.5... Base model:finetune:erayalp/qw... Conversational Curriculum-learning Dataset:erayalp/medium turkish... En Endpoints compatible Instruct Math Qwen2 Region:us Safetensors Supervised-fine-tuning Tr Turkish

Model Card on HF 🤗: https://huggingface.co/erayalp/qwen2.5-0.5b-instruct-SFT-v2-tr-math-medium

Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium Parameters and Internals

LLM Name	Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium
Repository 🤗	https://huggingface.co/erayalp/qwen2.5-0.5b-instruct-SFT-v2-tr-math-medium
Base Model(s)	erayalp/qwen2.5-0.5b-instruct-sft-v1-tr-math-easy erayalp/qwen2.5-0.5b-instruct-sft-v1-tr-math-easy
Model Size	0.5b
Required VRAM	2 GB
Updated	2026-05-11
Maintainer	erayalp
Model Type	qwen2
Instruction-Based	Yes
Model Files	2.0 GB 0.0 GB
Supported Languages	tr en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.50.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float32
Errors	replace

Rank the Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium 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

Best Alternatives to Qwen2.5 0.5B Instruct SFT V2 Tr Math Medium

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2 0.5B Abyme Merge3	128K / 1.3 GB	8	1
Qwen2 0.5B Abyme Merge2	128K / 0.3 GB	11	0
Qwen2.5 0.5B Instruct	64K / 1 GB	16	0
Chichu 2.0 500M Instruct	32K / 1 GB	212	2
Qwen2.5 0.5B Instruct	32K / 1 GB	6324790	572
Sakthai Context 0.5B Tools	32K / 1 GB	474	0
Qwen R1 0.5B	32K / 1 GB	202	2
Veda Labs 0.5B Instruct Base	32K / 1 GB	30	2
...ext Aware Abstention Qwen 0.5B	32K / 2 GB	48	0
Q SS 0.5B Reasoning Math	32K / 1 GB	12	2

Note: green Score (e.g. "73.2") means that the model is better than erayalp/qwen2.5-0.5b-instruct-SFT-v2-tr-math-medium.