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---
license: other
license_name: stem.ai.mtl
license_link: LICENSE
language:
- en
tags:
- phi-2
- electrical engineering
- Microsoft
datasets:
- STEM-AI-mtl/Electrical-engineering
- garage-bAInd/Open-Platypus
---
# Model Card for Model ID
This is the adapters from the LoRa fine-tuning of the phi-2 model from Microsoft. It was trained on the STEM-AI-mtl/Electrical-engineering dataset combined with garage-bAInd/Open-Platypus.
- **Developed by:** STEM.AI
- **Model type:** Q&A and code generation
- **Language(s) (NLP):** English
- **Finetuned from model [optional]:** microsoft/phi-2
### Direct Use
Q&A related to electrical engineering, and Kicad software. Creation of Python code in general, and for Kicad's scripting console.
Refer to microsoft/phi-2 model card for recommended prompt format.
## Training Details
### Training Data
Dataset related to electrical engineering: STEM-AI-mtl/Electrical-engineering
It is composed of queries, 65% about general electrical engineering, 25% about Kicad (EDA software) and 10% about Python code for Kicad's scripting console.
Combined with
Dataset related to STEM and NLP: garage-bAInd/Open-Platypus
### Training Procedure
LoRa script: https://github.com/STEM-ai/Phi-2/raw/4eaa6aaa2679427a810ace5a061b9c951942d66a/LoRa.py
A LoRa PEFT was performed on a 48 Gb A40 Nvidia GPU.
## Model Card Authors [optional]
STEM.AI: stem.ai.mtl@gmail.com
William Harbec
### Inference example
Standard: https://github.com/STEM-ai/Phi-2/raw/4eaa6aaa2679427a810ace5a061b9c951942d66a/chat.py
GPTQ format: https://github.com/STEM-ai/Phi-2/raw/ab1ced8d7922765344d824acf1924df99606b4fc/chat-GPTQ.py |