What are the hardware requirements for Qwen2.5 7B Instruct SFT Meme LoRA V7?

Qwen2.5 7B Instruct SFT Meme LoRA V7 requires approximately 15.2 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 7B Instruct SFT Meme LoRA V7 and how large is it?

Qwen2.5 7B Instruct SFT Meme LoRA V7 is developed by mimi1998, 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 Qwen2.5 7B Instruct SFT Meme LoRA V7?

Qwen2.5 7B Instruct SFT Meme LoRA V7 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 7B Instruct SFT Meme LoRA V7 by mimi1998 — VRAM 15.2GB, 128K context

Name: Qwen2.5 7B Instruct SFT Meme LoRA V7
Author: mimi1998

Qwen2.5 7B Instruct SFT Meme LoRA V7 is an open-source language model by mimi1998. Features: 7b LLM, VRAM: 15.2GB, Context: 128K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.19.

4bit En Endpoints compatible Instruct Lora Quantized Qwen2 Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/mimi1998/Qwen2.5-7B-Instruct-SFT-Meme-LoRA-V7

Qwen2.5 7B Instruct SFT Meme LoRA V7 Parameters and Internals

LLM Name	Qwen2.5 7B Instruct SFT Meme LoRA V7
Repository 🤗	https://huggingface.co/mimi1998/Qwen2.5-7B-Instruct-SFT-Meme-LoRA-V7
Base Model(s)	unsloth/qwen2.5-7b-unsloth-bnb-4bit unsloth/qwen2.5-7b-unsloth-bnb-4bit
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-07-19
Maintainer	mimi1998
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.52.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	152064
LoRA Model	Yes
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 7B Instruct SFT Meme LoRA V7 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 Qwen2.5 7B Instruct SFT Meme LoRA V7

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M 4bit	986K / 4.3 GB	444	11
...wen2.5 7B Instruct 1M Bnb 4bit	986K / 5.5 GB	267	1
Qwen2.5 7B Instruct 1M 8bit	986K / 8.1 GB	63	4
Qwen2.5 7B Instruct 1M 6bit	986K / 6.2 GB	52	2
...B Instruct 1M Unsloth Bnb 4bit	986K / 7.5 GB	37	3
Legal Qwen2.5 7B Sft	128K / 15.2 GB	111	0
Alisia 7B Instruct V1	128K / 15.4 GB	114	2
Gte Qwen2 7B Instruct 4bit DWQ	128K / 4.3 GB	88	3
WINTER FROST 2 PRO	32K / 15.2 GB	605	1
Qwen2.5 7B Legal Chatbot Exp1	32K / 15.2 GB	290	0

Note: green Score (e.g. "73.2") means that the model is better than mimi1998/Qwen2.5-7B-Instruct-SFT-Meme-LoRA-V7.