shkennedy33/count-cpt-v3
The shkennedy33/count-cpt-v3 is a 7.6 billion parameter Qwen2.5-based causal language model developed by shkennedy33, fine-tuned from unsloth/Qwen2.5-7B. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. It is designed for general language tasks, leveraging its Qwen2.5 architecture and efficient training methodology.
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Model Overview
The shkennedy33/count-cpt-v3 is a 7.6 billion parameter language model, fine-tuned by shkennedy33. It is based on the Qwen2.5-7B architecture, a robust foundation for various natural language processing tasks.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Qwen2.5-7B. - Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Use Cases
This model is suitable for applications requiring a capable 7.6 billion parameter language model, particularly where efficient fine-tuning processes are valued. Its Qwen2.5 foundation makes it versatile for tasks such as text generation, summarization, and question answering.