fevohh/WorldParser-0.5B-1903-16bit
WorldParser-0.5B-1903-16bit is a 0.5 billion parameter Qwen2.5-based instruction-tuned causal language model developed by fevohh. This model was finetuned from unsloth/Qwen2.5-0.5B-Instruct-unsloth-bnb-4bit using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its compact size for efficient deployment.
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WorldParser-0.5B-1903-16bit Overview
WorldParser-0.5B-1903-16bit is a compact 0.5 billion parameter instruction-tuned model developed by fevohh. It is based on the Qwen2.5 architecture and was finetuned from unsloth/Qwen2.5-0.5B-Instruct-unsloth-bnb-4bit. A key aspect of its development is the utilization of Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
Key Characteristics
- Architecture: Qwen2.5-based causal language model.
- Parameter Count: 0.5 billion parameters, making it suitable for resource-constrained environments.
- Training Efficiency: Benefited from Unsloth for accelerated finetuning.
- License: Distributed under the Apache-2.0 license.
Good For
- Applications requiring a lightweight yet capable instruction-following model.
- Scenarios where efficient deployment and faster inference are critical due to its smaller size.
- Developers interested in models finetuned with Unsloth for optimized training.