Overview

This model, j05hr3d/Llama-3.2-3B-Instruct-C_M_T-ALPACA-SEED999, is an instruction-tuned variant of the meta-llama/Llama-3.2-3B-Instruct base model. It features 3.2 billion parameters and supports a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating more extensive responses. The fine-tuning process utilized the TRL (Transformer Reinforcement Learning) library, specifically employing Supervised Fine-Tuning (SFT) to enhance its ability to follow instructions effectively.

Key Capabilities

• Instruction Following: Optimized through SFT to understand and execute user instructions.
• Extended Context: Benefits from a 32768-token context window, allowing for detailed conversations and processing of longer documents.
• Base Model Heritage: Built upon the robust Llama-3.2-3B-Instruct architecture, inheriting its foundational language understanding.

Training Details

The model was fine-tuned using the TRL framework (version 0.27.1) with Transformers (4.57.6), Pytorch (2.10.0+cu128), Datasets (4.8.4), and Tokenizers (0.22.2). The training procedure involved Supervised Fine-Tuning (SFT).

Good For

• General-purpose instruction-following tasks.
• Applications requiring a balance of model size and performance for conversational AI or text generation where instruction adherence is crucial.
• Scenarios benefiting from a larger context window for more comprehensive interactions.