bilalhassan0099/my_modelV1
my_modelV1 is a 3.1 billion parameter instruction-tuned causal language model developed by bilalhassan0099, finetuned from unsloth/Qwen2.5-3B-Instruct-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
bilalhassan0099/my_modelV1 is a 3.1 billion parameter instruction-tuned language model developed by bilalhassan0099. It is finetuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model, leveraging the Qwen2.5 architecture.
Key Characteristics
- Efficient Training: This model was trained with Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Base Model: Built upon the Qwen2.5-3B-Instruct architecture, known for its strong performance in instruction-following tasks.
- Parameter Count: With 3.1 billion parameters, it offers a balance between performance and computational efficiency.
- Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more extensive outputs.
Use Cases
This model is suitable for a variety of general instruction-following applications where efficient performance from a smaller model is desired. Its optimized training process suggests potential for rapid iteration and deployment in scenarios requiring quick fine-tuning or deployment of instruction-tuned models.