nikinetrahutama/afx-ai-llama-chat-model-sqlprompt-11
The nikinetrahutama/afx-ai-llama-chat-model-sqlprompt-11 is a 7 billion parameter Llama-based model, fine-tuned using 4-bit quantization (nf4) and bfloat16 compute dtype. This model is specifically optimized for chat interactions, likely focusing on SQL prompt generation given its name. Its training procedure utilized PEFT for efficient adaptation.
Loading preview...
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:
bitsandbyteswas 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:
bfloat16was 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.