Model Overview

gjyotin305/Llama-3.2-3B-Instruct_old_sft_alpaca_001 is a 3.2 billion parameter instruction-tuned language model, developed by gjyotin305. It is fine-tuned from the unsloth/Llama-3.2-3B-Instruct base model, leveraging the Unsloth library for accelerated training.

Key Characteristics

• Architecture: Llama-3.2-3B-Instruct base.
• Parameter Count: 3.2 billion parameters.
• Context Length: Supports a substantial context window of 32768 tokens.
• Training Efficiency: Fine-tuned with Unsloth and Huggingface's TRL library, resulting in 2x faster training compared to standard methods.
• License: Distributed under the Apache-2.0 license.

Use Cases

This model is particularly well-suited for applications requiring:

• Instruction Following: Designed for tasks where the model needs to adhere to specific instructions.
• Efficient Deployment: Its 3.2 billion parameter size makes it suitable for scenarios where computational resources are a consideration, while still offering a large context window.
• Accelerated Development: Benefits from the Unsloth framework, indicating potential for rapid iteration and deployment in projects.