Model Overview

KobeBeef67/llama32-3b-finetuned is a 3.2 billion parameter Llama-based language model developed by KobeBeef67. This model is a finetuned version of unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit and was specifically optimized for training speed.

Key Characteristics

• Architecture: Llama-based, 3.2 billion parameters.
• Context Length: Supports a substantial context window of 32768 tokens.
• Training Efficiency: Achieved 2x faster training by leveraging the Unsloth library in conjunction with Huggingface's TRL library.
• License: Distributed under the Apache-2.0 license.

Intended Use Cases

This model is suitable for applications where a compact yet capable Llama-based model with a large context window is beneficial. Its optimized training process suggests potential for efficient deployment and further fine-tuning for specific tasks.