Piyush445/qwen2.53Bmerged-f
Piyush445/qwen2.53Bmerged-f is a 3.1 billion parameter Qwen2-based causal language model developed by Piyush445. This model was finetuned from unsloth/Qwen2.5-3B-Instruct-bnb-4bit using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology to provide a capable model within its parameter class.
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Model Overview
Piyush445/qwen2.53Bmerged-f is a 3.1 billion parameter language model developed by Piyush445. It is finetuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model, leveraging the Unsloth library and Huggingface's TRL for efficient training. This approach allowed for a 2x speedup in the finetuning process.
Key Characteristics
- Base Architecture: Qwen2.5
- Parameter Count: 3.1 billion
- Training Efficiency: Utilizes Unsloth for accelerated finetuning, resulting in 2x faster training compared to standard methods.
- Context Length: Supports a context window of 32,768 tokens.
Intended Use Cases
This model is suitable for a variety of general-purpose language generation and understanding tasks, particularly where a compact yet capable model is desired. Its efficient training process suggests it could be a good candidate for applications requiring rapid iteration or deployment on resource-constrained environments.