shkennedy33/count-cpt-v2
shkennedy33/count-cpt-v2 is a 7.6 billion parameter Qwen2.5 model developed by shkennedy33, fine-tuned from unsloth/Qwen2.5-7B. This model was trained significantly faster using Unsloth and Huggingface's TRL library. It is designed as a general-purpose language model with a 32768 token context length, benefiting from optimized training efficiency.
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Model Overview
shkennedy33/count-cpt-v2 is a 7.6 billion parameter language model, fine-tuned by shkennedy33 from the unsloth/Qwen2.5-7B base model. It leverages the Qwen2.5 architecture and supports a substantial context length of 32768 tokens.
Key Capabilities
- Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Qwen2.5 Architecture: Benefits from the robust capabilities of the Qwen2.5 model family.
- Extended Context: Features a 32768 token context window, suitable for processing longer inputs and maintaining conversational coherence over extended interactions.
When to Use This Model
This model is particularly suitable for developers seeking a Qwen2.5-based solution that has undergone an optimized and accelerated fine-tuning process. Its efficient development makes it a strong candidate for applications where rapid iteration and deployment of fine-tuned models are critical, while still offering the performance characteristics of the Qwen2.5 family.