What are the hardware requirements for Zephyr 7B Ipo Qlora V0 Merged?

Zephyr 7B Ipo Qlora V0 Merged requires approximately 28.9 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 Zephyr 7B Ipo Qlora V0 Merged and how large is it?

Zephyr 7B Ipo Qlora V0 Merged is developed by DUAL-GPO, 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 Zephyr 7B Ipo Qlora V0 Merged?

Zephyr 7B Ipo Qlora V0 Merged is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Zephyr 7B Ipo Qlora V0 Merged by DUAL-GPO — VRAM 28.9GB, 32K context

Name: Zephyr 7B Ipo Qlora V0 Merged
Author: DUAL-GPO

Zephyr 7B Ipo Qlora V0 Merged is an open-source language model by DUAL-GPO. Features: 7b LLM, VRAM: 28.9GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.18.

Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/DUAL-GPO/zephyr-7b-ipo-qlora-v0-merged

Zephyr 7B Ipo Qlora V0 Merged Parameters and Internals

Training Details

Data Sources:

HuggingFaceH4/ultrafeedback_binarized

Methodology:

Fine-tuning using IPO

LLM Name	Zephyr 7B Ipo Qlora V0 Merged
Repository 🤗	https://huggingface.co/DUAL-GPO/zephyr-7b-ipo-qlora-v0-merged
Model Size	7b
Required VRAM	28.9 GB
Updated	2026-09-07
Maintainer	DUAL-GPO
Model Type	mistral
Model Files	5.0 GB: 1-of-6 4.9 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 4.8 GB: 5-of-6 4.2 GB: 6-of-6
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float32

Rank the Zephyr 7B Ipo Qlora V0 Merged 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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MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
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SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
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MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
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Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than DUAL-GPO/zephyr-7b-ipo-qlora-v0-merged.