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
task_categories:
- question-answering
- text-generation
pipeline_tag: text-generation
widget:
- text: Enter your instruction here
inference: true
auto_sample: true
library_tag: transformers
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: 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
STEM.AI: stem.ai.mtl@gmail.com William Harbec
Inference example
Standard: https://github.com/STEM-ai/Phi-2/blob/4eaa6aaa2679427a810ace5a061b9c951942d66a/chat.py
GPTQ format: https://github.com/STEM-ai/Phi-2/blob/ab1ced8d7922765344d824acf1924df99606b4fc/chat-GPTQ.py