jessiewtx/fdr-slm-v1
The jessiewtx/fdr-slm-v1 is a 2 billion parameter Qwen3-based causal language model developed by jessiewtx. This model was finetuned from unsloth/qwen3-1.7b-unsloth-bnb-4bit, leveraging Unsloth and Huggingface's TRL library for accelerated training. It is optimized for tasks benefiting from efficient training methodologies and a 32768 token context length.
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Model Overview
The jessiewtx/fdr-slm-v1 is a 2 billion parameter language model based on the Qwen3 architecture. It was developed by jessiewtx and finetuned from the unsloth/qwen3-1.7b-unsloth-bnb-4bit model.
Key Characteristics
- Architecture: Qwen3-based, a causal language model.
- Parameter Count: 2 billion parameters.
- Context Length: Supports a context length of 32768 tokens.
- Training Efficiency: The model was trained using Unsloth and Huggingface's TRL library, enabling a 2x faster finetuning process compared to standard methods.
Use Cases
This model is suitable for applications requiring a compact yet capable language model, particularly where efficient training and deployment are priorities. Its Qwen3 base and optimized finetuning process make it a strong candidate for various natural language processing tasks.