CriteriaPO/llama3.2-3b-sft-10

Overview

CriteriaPO/llama3.2-3b-sft-10 is a 3 billion parameter language model developed by CriteriaPO. It is a fine-tuned variant of Meta's Llama-3.2-3B, specifically optimized through Supervised Fine-Tuning (SFT) using the TRL library. This process aims to improve the model's performance in understanding and responding to user instructions.

Key Capabilities

• Instruction Following: Enhanced ability to generate responses based on given prompts and instructions due to SFT.
• Text Generation: Capable of producing coherent and contextually relevant text for various applications.
• Foundation Model: Built upon the Llama-3.2-3B architecture, providing a solid base for language understanding and generation.

Training Details

The model was trained using the TRL (Transformer Reinforcement Learning) framework, version 0.12.2. The training procedure involved SFT, which typically uses high-quality instruction-response pairs to guide the model's behavior. This fine-tuning process leverages modern deep learning frameworks including Transformers (4.46.3), Pytorch (2.1.2+cu121), Datasets (3.1.0), and Tokenizers (0.20.3).

Good For

• General Text Generation: Suitable for tasks like answering questions, creative writing, and conversational AI.
• Instruction-based Tasks: Excels in scenarios where the model needs to adhere to specific user instructions or prompts.