What are the hardware requirements for Phi 2 Electrical Engineering?

Phi 2 Electrical Engineering requires approximately 5.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Phi 2 Electrical Engineering is developed by STEM-AI-mtl, a model with 2.8b 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 Phi 2 Electrical Engineering?

Phi 2 Electrical Engineering 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 by STEM-AI-mtl — VRAM 5.6GB

Name: Phi 2 Electrical Engineering
Author: STEM-AI-mtl

Phi 2 Electrical Engineering is an open-source language model by STEM-AI-mtl. Features: 2.8b LLM, VRAM: 5.6GB, License: other, LLM Explorer Score: 0.11.

Custom code Dataset:garage-baind/open-plat... Dataset:stem-ai-mtl/electrical... Electrical engineering En Endpoints compatible Lora Microsoft Phi Phi-2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/STEM-AI-mtl/phi-2-electrical-engineering

Phi 2 Electrical Engineering Benchmarks

LLME Score: 0.11386

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Phi 2 Electrical Engineering (STEM-AI-mtl/phi-2-electrical-engineering)

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Phi 2 Electrical Engineering Parameters and Internals

Model Type

Q&A, code generation

Use Cases

Areas:

electrical engineering

Applications:

Q&A related to electrical engineering and Kicad software, creation of Python code for Kicad's scripting console

Supported Languages

en (native)

Training Details

Data Sources:

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

Methodology:

LoRa PEFT

Hardware Used:

48 Gb A40 Nvidia GPU

LLM Name	Phi 2 Electrical Engineering
Repository 🤗	https://huggingface.co/STEM-AI-mtl/phi-2-electrical-engineering
Model Size	2.8b
Required VRAM	5.6 GB
Updated	2026-04-24
Maintainer	STEM-AI-mtl
Model Files	0.1 GB 5.0 GB: 1-of-2 0.6 GB: 2-of-2
Supported Languages	en
Model Architecture	AutoModelForCausalLM
License	other
Model Max Length	2048
Is Biased	none
Tokenizer Class	CodeGenTokenizer
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	fc2\|fc1\|Wqkv
LoRA Alpha	64
LoRA Dropout	0.05
R Param	32

Quantized Models of the Phi 2 Electrical Engineering

Model	Likes	Downloads	VRAM
... 2 Electrical Engineering GGUF	18	1288	1 GB
... 2 Electrical Engineering GPTQ	7	32	1 GB

Best Alternatives to Phi 2 Electrical Engineering

Best Alternatives	Context / RAM	Downloads	Likes
Zephyr Rag Agent Webgpt	0K / 40.1 GB	1	1
Phi Med V1	0K / 11.1 GB	4	1
Phi2 Bunny	0K / 5.6 GB	673	3
Phi2 Sqlcoder	0K / 5.6 GB	160	7

Note: green Score (e.g. "73.2") means that the model is better than STEM-AI-mtl/phi-2-electrical-engineering.

Rank the Phi 2 Electrical Engineering Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Phi 2 Electrical Engineering by STEM-AI-mtl