What are the hardware requirements for Phi 2 Electrical Engineering GGUF?

Phi 2 Electrical Engineering GGUF requires approximately 1.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Phi 2 Electrical Engineering GGUF and how large is it?

Phi 2 Electrical Engineering GGUF is developed by TheBloke. 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 Phi 2 Electrical Engineering GGUF?

Phi 2 Electrical Engineering GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Phi 2 Electrical Engineering GGUF by TheBloke — VRAM 1.1GB

Name: Phi 2 Electrical Engineering GGUF
Rating: 3 (1 reviews)
Author: TheBloke

Phi 2 Electrical Engineering GGUF is an open-source language model by TheBloke. Features: LLM, VRAM: 1.1GB, License: other, Quantized, LLM Explorer Score: 0.11.

Base model:quantized:stem-ai-m... Base model:stem-ai-mtl/phi-2-e... Dataset:garage-baind/open-plat... Dataset:stem-ai-mtl/electrical... Electrical engineering En Gguf Microsoft Phi-2 Phi-msft Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/phi-2-electrical-engineering-GGUF

Phi 2 Electrical Engineering GGUF Parameters and Internals

Model Type

Q&A, code generation

Additional Notes

This model was fine-tuned using LoRa technique for electrical engineering Q&A and Python code generation related to KiCad software.

Supported Languages

en (fluent)

Training Details

Data Sources:

STEM-AI-mtl/Electrical-engineering, garage-bAInd/Open-Platypus

Methodology:

LoRa fine-tuning

Hardware Used:

48 Gb A40 Nvidia GPU

LLM Name	Phi 2 Electrical Engineering GGUF
Repository 🤗	https://huggingface.co/TheBloke/phi-2-electrical-engineering-GGUF
Model Name	Phi 2 Electrical Engineering
Model Creator	mod
Base Model(s)	Phi 2 Electrical Engineering STEM-AI-mtl/phi-2-electrical-engineering
Required VRAM	1.1 GB
Updated	2026-07-07
Maintainer	TheBloke
Model Type	phi-msft
Model Files	1.1 GB 1.6 GB 1.4 GB 1.2 GB 1.6 GB 1.7 GB 1.6 GB 1.9 GB 2.0 GB 1.9 GB 2.3 GB 3.0 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	other

Rank the Phi 2 Electrical Engineering GGUF 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 TheBloke/phi-2-electrical-engineering-GGUF.