--- 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