What are the hardware requirements for Chemeng Qwen Math 7B 24 1 100 1 Nonmath?

Chemeng Qwen Math 7B 24 1 100 1 Nonmath requires approximately 15.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Chemeng Qwen Math 7B 24 1 100 1 Nonmath and how large is it?

Chemeng Qwen Math 7B 24 1 100 1 Nonmath is developed by kms7530, a model with 7b 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 Chemeng Qwen Math 7B 24 1 100 1 Nonmath?

Chemeng Qwen Math 7B 24 1 100 1 Nonmath is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Chemeng Qwen Math 7B 24 1 100 1 Nonmath by kms7530 — VRAM 15.2GB

Name: Chemeng Qwen Math 7B 24 1 100 1 Nonmath
Author: kms7530

Chemeng Qwen Math 7B 24 1 100 1 Nonmath is an open-source language model by kms7530. Features: 7b LLM, VRAM: 15.2GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.2.

4bit Base model:quantized:unsloth/q... Base model:unsloth/qwen2.5-mat... Conversational Dataset:kms7530/chemeng En Endpoints compatible Gguf Instruct Lora Pytorch Quantized Qwen2 Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/kms7530/chemeng_qwen-math-7b_24_1_100_1_nonmath

Chemeng Qwen Math 7B 24 1 100 1 Nonmath Parameters and Internals

LLM Name	Chemeng Qwen Math 7b 24 1 100 1 Nonmath
Repository 🤗	https://huggingface.co/kms7530/chemeng_qwen-math-7b_24_1_100_1_nonmath
Base Model(s)	unsloth/Qwen2.5-Math-7B-Instruct-bnb-4bit unsloth/Qwen2.5-Math-7B-Instruct-bnb-4bit
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-08-04
Maintainer	kms7530
Instruction-Based	Yes
Model Files	0.2 GB 4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4 4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4 4.7 GB 5.4 GB 8.1 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|4bit
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Model Max Length	4096
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	down_proj\|o_proj\|gate_proj\|q_proj\|v_proj\|k_proj\|up_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16
Errors	replace

Rank the Chemeng Qwen Math 7B 24 1 100 1 Nonmath capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
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Data Analysis and Insight Generation
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Note: green Score (e.g. "73.2") means that the model is better than kms7530/chemeng_qwen-math-7b_24_1_100_1_nonmath.