What are the hardware requirements for Granite 4.2 8B Msvc2008 Decomp Lora?

Granite 4.2 8B Msvc2008 Decomp Lora requires approximately 0.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Granite 4.2 8B Msvc2008 Decomp Lora and how large is it?

Granite 4.2 8B Msvc2008 Decomp Lora is developed by gavinbrow, a model with 8b 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 Granite 4.2 8B Msvc2008 Decomp Lora?

Granite 4.2 8B Msvc2008 Decomp Lora is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Granite 4.2 8B Msvc2008 Decomp Lora by gavinbrow — VRAM 0.8GB

Name: Granite 4.2 8B Msvc2008 Decomp Lora
Author: gavinbrow

Granite 4.2 8B Msvc2008 Decomp Lora is an open-source language model by gavinbrow. Features: 8b LLM, VRAM: 0.8GB, License: apache-2.0.

Adapter Base model:adapter:ibm-granite... Base model:ibm-granite/granite... Decompilation Finetuned Granite Lora Msvc Peft Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/gavinbrow/granite-4.2-8b-msvc2008-decomp-lora

Granite 4.2 8B Msvc2008 Decomp Lora Parameters and Internals

LLM Name	Granite 4.2 8B Msvc2008 Decomp Lora
Repository 🤗	https://huggingface.co/gavinbrow/granite-4.2-8b-msvc2008-decomp-lora
Base Model(s)	ibm-granite/granite-4.2-8b ibm-granite/granite-4.2-8b
Model Size	8b
Required VRAM	0.8 GB
Updated	2026-10-27
Maintainer	gavinbrow
Model Files	0.8 GB
Model Architecture	Adapter
License	apache-2.0
Is Biased	none
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	up_proj\|down_proj\|k_proj\|q_proj\|o_proj\|gate_proj\|v_proj
LoRA Alpha	64
LoRA Dropout	0.05
R Param	64

Rank the Granite 4.2 8B Msvc2008 Decomp Lora 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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Note: green Score (e.g. "73.2") means that the model is better than gavinbrow/granite-4.2-8b-msvc2008-decomp-lora.