Quantization made by Richard Erkhov.
A unique, deployable and efficient 2.7 billion parameters model in the field of electrical engineering. This repo contains 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.
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.
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.
In additionataset related to STEM and NLP:
garage-bAInd/Open-PlatypusA LoRa PEFT was performed on a 48 Gb A40 Nvidia GPU.
