shkennedy33/count-cpt-v1
The shkennedy33/count-cpt-v1 is a 7.6 billion parameter Qwen2.5 model, developed by shkennedy33, that has been finetuned using Unsloth and Huggingface's TRL library. This model benefits from 2x faster training, making it efficient for specific tasks. It is designed for applications requiring a performant yet efficiently trained language model.
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Model Overview
The shkennedy33/count-cpt-v1 is a 7.6 billion parameter language model based on the Qwen2.5 architecture. Developed by shkennedy33, this model was finetuned from unsloth/Qwen2.5-7B using the Unsloth library in conjunction with Huggingface's TRL library.
Key Characteristics
- Architecture: Qwen2.5-7B base model.
- Parameter Count: 7.6 billion parameters.
- Training Efficiency: Finetuned with Unsloth, enabling 2x faster training compared to standard methods.
- Context Length: Supports a context length of 32768 tokens.
- License: Released under the Apache-2.0 license.
Use Cases
This model is suitable for developers looking for a Qwen2.5-based solution that has undergone efficient finetuning. Its optimized training process suggests potential benefits for applications where rapid iteration and deployment of finetuned models are crucial.