dellaneirasyfd/qwen-indo-lora
The dellaneirasyfd/qwen-indo-lora is a 3.1 billion parameter Qwen2-based language model, fine-tuned by dellaneirasyfd. This model leverages Unsloth and Huggingface's TRL library for accelerated training. It is designed for general language tasks, offering a balance of performance and efficiency for applications requiring a smaller footprint.
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Model Overview
The dellaneirasyfd/qwen-indo-lora is a 3.1 billion parameter language model, fine-tuned by dellaneirasyfd. It is based on the Qwen2 architecture and was developed using Unsloth and Huggingface's TRL library, which enabled faster training.
Key Characteristics
- Base Model: Qwen2-based, specifically fine-tuned from
unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit. - Parameter Count: 3.1 billion parameters, offering a compact yet capable model size.
- Training Efficiency: Utilizes Unsloth for 2x faster training, indicating an optimized development process.
- Context Length: Supports a context length of 32768 tokens, allowing for processing of substantial input sequences.
Potential Use Cases
This model is suitable for various natural language processing tasks where a smaller, efficient model is preferred. Its Qwen2 base and fine-tuning suggest capabilities in areas such as:
- Text generation and completion.
- Instruction-following tasks.
- Applications requiring a balance between performance and computational resources.