What are the hardware requirements for Herbert V0.5?

Herbert V0.5 requires approximately 0.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Herbert V0.5 and how large is it?

Herbert V0.5 is developed by leinenterprises, a model with 27b 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 Herbert V0.5?

Herbert V0.5 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Herbert V0.5 by leinenterprises — VRAM 0.9GB

Name: Herbert V0.5
Author: leinenterprises

Herbert V0.5 is an open-source language model by leinenterprises. Features: 27b LLM, VRAM: 0.9GB, License: apache-2.0, LLM Explorer Score: 0.29.

Adapter Base model:adapter:qwen/qwen3.... Base model:qwen/qwen3.8-27b Decision-index Finetuned Image-text-to-text Jev Lora Peft Region:us Safetensors System-one Typed-decisions Vision Zero-shot-classification

Model Card on HF 🤗: https://huggingface.co/leinenterprises/Herbert_v0.5

Herbert V0.5 Parameters and Internals

LLM Name	Herbert V0.5
Repository 🤗	https://huggingface.co/leinenterprises/Herbert_v0.5
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	0.9 GB
Updated	2026-10-21
Maintainer	leinenterprises
Model Files	0.9 GB
Model Architecture	Adapter
License	apache-2.0
Is Biased	none
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	^\|(\|?\|!\|.\|\|v\|i\|s\|u\|a\|l\|)\|.\|\|\\|.\|(\|q\|_\|p\|r\|o\|j\|\|\|k\|_\|p\|r\|o\|j\|\|\|v\|_\|p\|r\|o\|j\|\|\|o\|_\|p\|r\|o\|j\|\|\|g\|a\|t\|e\|_\|p\|r\|o\|j\|\|\|u\|p\|_\|p\|r\|o\|j\|\|\|d\|o\|w\|n\|_\|p\|r\|o\|j\|\|\|i\|n\|_\|p\|r\|o\|j\|_\|q\|k\|v\|\|\|i\|n\|_\|p\|r\|o\|j\|_\|z\|\|\|o\|u\|t\|_\|p\|r\|o\|j\|)\|$
LoRA Alpha	64
LoRA Dropout	0
R Param	32

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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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