minsu0567/Uni-IAD-R2-Qwen3.5-GRPO-si-answer-last
The minsu0567/Uni-IAD-R2-Qwen3.5-GRPO-si-answer-last is a 4.5 billion parameter Qwen3.5-based causal language model developed by minsu0567. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed compared to standard methods. It is specifically optimized for tasks related to its fine-tuning objective, building upon the minsu0567/Uni-IAD-R2-Qwen3.5-si-answer-last base model.
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Model Overview
The minsu0567/Uni-IAD-R2-Qwen3.5-GRPO-si-answer-last is a 4.5 billion parameter language model, developed by minsu0567. It is a fine-tuned variant of the minsu0567/Uni-IAD-R2-Qwen3.5-si-answer-last base model.
Key Characteristics
- Architecture: Based on the Qwen3.5 model family.
- Parameter Count: 4.5 billion parameters.
- Context Length: Supports a context length of 32768 tokens.
- Training Efficiency: This model was fine-tuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
Intended Use
This model is suitable for applications requiring a Qwen3.5-based model that has undergone specific fine-tuning for particular tasks, leveraging the efficiency gains from Unsloth. Developers can utilize this model for tasks aligned with its fine-tuning objective, benefiting from its optimized training methodology.