nashirwahyudi/qwen2.5-3b-instruct-alpaca-indo-uu
The nashirwahyudi/qwen2.5-3b-instruct-alpaca-indo-uu is a 3.1 billion parameter instruction-tuned language model developed by nashirwahyudi. It is finetuned from unsloth/Qwen2.5-3B-Instruct-bnb-4bit, leveraging Unsloth and Huggingface's TRL library for faster training. This model is designed for general language tasks, building upon the Qwen2.5 architecture.
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Model Overview
The nashirwahyudi/qwen2.5-3b-instruct-alpaca-indo-uu is a 3.1 billion parameter instruction-tuned language model. It was developed by nashirwahyudi and is finetuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model.
Key Characteristics
- Base Model: Built upon the Qwen2.5-3B-Instruct architecture.
- Training Efficiency: Utilizes Unsloth and Huggingface's TRL library, enabling a 2x faster training process compared to standard methods.
- Parameter Count: Features 3.1 billion parameters, offering a balance between performance and computational efficiency.
- License: Distributed under the Apache-2.0 license, allowing for broad usage and modification.
Use Cases
This model is suitable for a variety of general-purpose natural language processing tasks, particularly those benefiting from instruction-following capabilities. Its efficient training methodology suggests it could be a good candidate for applications where rapid iteration or deployment on resource-constrained environments is important.