SynapseLLM, a significant achievement by WebraftAI, represents a series of large language AI models designed to create robust, generalized, and decentralized information systems. This repository specifically houses the SynapseLLM finetuned version of Mistral. The finetuning process is conducted on a custom dataset, albeit limited in scope, focusing on code and normal question-answering scenarios. This adaptation showcases the model's versatility and applicability within specific domains, contributing to the broader landscape of AI advancements.
Model Details
SynapseLLM:
Parameters: 7B
Learning rate: 2e-4
Adapter used: Qlora
Precision: float16
Batch size: 32
Maximum gradient normal: 0.3
Optimizer: paged_adamw_32bit
Warmup Ratio: 0.03
Step(s) (trained): 100
Epoch(s) (trained): 1
Model Description
This is a 7b parameter, decoder only transformer based finetuned model on Chat Q/A and Code instructions. It's a preview finetune on Mistral 7B v0.1 on a sample dataset of 140k rows comprising of 73k Code and 67k General Q/A (Through GPT-4). This is a full model merged and compiled with trained adapters, so you can easily load this through transformers.
