Birbal: An efficient 7B instruct-model fine-tuned with curated datasets

Understand

LLMOps incur significant costs due to hardware requirements, hindering their widespread accessibility.

• Additionally, a lack of transparency in model training methods and data contributes to the majority of models being non-reproducible.
• To tackle these challenges, the LLM Efficiency Challenge was introduced at NeurIPS Workshop, aiming to adapt foundation models on a diverse set of tasks via fine-tuning on a single GPU (RTX 4090 or A100 with 40GB) within a 24-hour timeframe.
• In this system description paper, we introduce Birbal, our Mistral-7B based winning model, fine-tuned on a single RTX 4090 for 16 hours.