Model Overview

This model, j05hr3d/Llama-3.2-1B-Instruct-C_M_T-SAM-AUX_CT_CE-RHO0_05lr2, is a 1 billion parameter instruction-tuned language model. It is built upon the meta-llama/Llama-3.2-1B-Instruct base model, indicating its foundation in the Llama 3.2 architecture.

Key Characteristics

• Base Model: Fine-tuned from meta-llama/Llama-3.2-1B-Instruct.
• Parameter Count: 1 billion parameters, offering a balance between performance and computational efficiency.
• Training Method: Utilizes Supervised Fine-Tuning (SFT) via the TRL library.
• Context Length: Supports a context window of 32768 tokens, allowing for processing of substantial input lengths.

Intended Use Cases

This model is primarily designed for general instruction-following tasks, leveraging its instruction-tuned nature. Its 1B parameter size makes it suitable for:

• Quick prototyping and development.
• Applications where computational resources are limited.
• Tasks requiring efficient text generation and understanding based on user prompts.

Training Details

The model was trained using specific versions of popular machine learning frameworks:

• TRL: 0.27.1
• Transformers: 4.57.6
• Pytorch: 2.10.0+cu128
• Datasets: 4.8.4
• Tokenizers: 0.22.2