What are the hardware requirements for Yell Qwen2.5 7B Stock?

Yell Qwen2.5 7B Stock requires approximately 15.2 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 Yell Qwen2.5 7B Stock and how large is it?

Yell Qwen2.5 7B Stock is developed by marcuscedricridia, 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 Yell Qwen2.5 7B Stock?

Yell Qwen2.5 7B Stock is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Yell Qwen2.5 7B Stock by marcuscedricridia — VRAM 15.2GB, 32K context

Name: Yell Qwen2.5 7B Stock
Author: marcuscedricridia

Yell Qwen2.5 7B Stock is an open-source language model by marcuscedricridia. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, Instruction-Based, Merged, LLM Explorer Score: 0.17.

Merged Model Arxiv:2403.19522 Base model:cran-may/t.e-8.1 Base model:deepseek-ai/deepsee... Base model:huihui-ai/deepseek-... Base model:marcuscedricridia/y... Base model:qwen/qwen2.5-7b-ins... Conversational Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/marcuscedricridia/Yell-Qwen2.5-7B-Stock

Yell Qwen2.5 7B Stock Parameters and Internals

LLM Name	Yell Qwen2.5 7B Stock
Repository 🤗	https://huggingface.co/marcuscedricridia/Yell-Qwen2.5-7B-Stock
Base Model(s)	...Distill Qwen 7B Abliterated V2 Cran-May/T.E-8.1 Qwen/Qwen2.5-7B-Instruct DeepSeek R1 Distill Qwen 7B marcuscedricridia/Yell-Qwen2.5-7B-Coder huihui-ai/DeepSeek-R1-Distill-Qwen-7B-abliterated-v2 Cran-May/T.E-8.1 Qwen/Qwen2.5-7B-Instruct deepseek-ai/DeepSeek-R1-Distill-Qwen-7B marcuscedricridia/Yell-Qwen2.5-7B-Coder
Merged Model	Yes
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-07-19
Maintainer	marcuscedricridia
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-4 4.9 GB: 2-of-4 5.0 GB: 3-of-4 0.3 GB: 4-of-4
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the Yell Qwen2.5 7B Stock 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

Best Alternatives to Yell Qwen2.5 7B Stock

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Rewnozom	986K / 30.5 GB	742	1
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen2.5 7B RRP 1M	986K / 15.2 GB	5	6
Qwen2.5 7B CelestialHarmony 1M	986K / 14.8 GB	8	7
Q2.5 Instruct 1M Harmony	986K / 15.2 GB	4	2
Impish QWEN 7B 1M	986K / 15.2 GB	4	6
COCO 7B Instruct 1M	986K / 15.2 GB	9	4
Apollo 7B	986K / 15.2 GB	8	0
Graph R1 7B	986K / 15.3 GB	7	3

Note: green Score (e.g. "73.2") means that the model is better than marcuscedricridia/Yell-Qwen2.5-7B-Stock.