What are the hardware requirements for Merged DPO Model?

Merged DPO Model requires approximately 6.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Merged DPO Model and how large is it?

Merged DPO Model is developed by Veture, a model with 1.7b 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 Merged DPO Model?

Merged DPO Model is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Merged DPO Model by Veture — VRAM 6.8GB

Name: Merged DPO Model
Author: Veture

Merged DPO Model is an open-source language model by Veture. Features: 1.7b LLM, VRAM: 6.8GB, Merged, LLM Explorer Score: 0.13.

Merged Model Arxiv:1910.09700 Bloom Endpoints compatible Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Veture/merged_dpo_model

Merged DPO Model Parameters and Internals

LLM Name	Merged DPO Model
Repository 🤗	https://huggingface.co/Veture/merged_dpo_model
Merged Model	Yes
Model Size	1.7b
Required VRAM	6.8 GB
Updated	2026-05-11
Maintainer	Veture
Model Type	bloom
Model Files	4.9 GB: 1-of-2 1.9 GB: 2-of-2
Model Architecture	BloomForCausalLM
Transformers Version	4.42.0.dev0
Tokenizer Class	BloomTokenizer
Padding Token	<pad>
Vocabulary Size	250880
Torch Data Type	float32

Rank the Merged DPO Model 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

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Merged AutoGPTQ DPO	0K / 2.3 GB	5	0
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