Model Overview

The nikinetrahutama/afx-ai-llama-chat-model-sqlprompt-11 is a 7 billion parameter language model built on the Llama architecture. It has been fine-tuned with a focus on chat applications, particularly indicated by its name to handle SQL prompt generation.

Training Details

The model underwent a specific training procedure utilizing bitsandbytes quantization. Key aspects of its training include:

• Quantization Method: bitsandbytes was used for efficient training and deployment.
• Quantization Type: It was trained with 4-bit quantization (bnb_4bit_quant_type: nf4) and double quantization (bnb_4bit_use_double_quant: True).
• Compute Dtype: bfloat16 was used for computation during the 4-bit quantization process.
• Framework: PEFT (version 0.5.0.dev0) was employed, suggesting an efficient fine-tuning approach.

Potential Use Cases

Given its architecture and naming convention, this model is likely well-suited for:

• Generating SQL queries from natural language prompts in a chat interface.
• Assisting developers with database interactions through conversational AI.
• Applications requiring efficient, quantized Llama-based models for chat-oriented tasks.