dwt012/vit2sql-q-grpo-reward-dapo-loss
dwt012/vit2sql-q-grpo-reward-dapo-loss is a 7.6 billion parameter Qwen2-based causal language model developed by dwt012, fine-tuned from unsloth/qwen2.5-coder-7b-instruct-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for specific applications related to its fine-tuning, leveraging its Qwen2 architecture for language generation tasks.
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Model Overview
dwt012/vit2sql-q-grpo-reward-dapo-loss is a 7.6 billion parameter language model developed by dwt012. It is fine-tuned from the unsloth/qwen2.5-coder-7b-instruct-bnb-4bit base model, indicating a foundation in code-related instruction following and generation. The model leverages the Qwen2 architecture, known for its strong performance across various language tasks.
Key Training Details
- Base Model: Fine-tuned from
unsloth/qwen2.5-coder-7b-instruct-bnb-4bit. - Training Efficiency: The fine-tuning process was significantly optimized, achieving 2x faster training speeds by utilizing Unsloth and Huggingface's TRL library. This highlights an efficient approach to model development and iteration.
Potential Use Cases
Given its fine-tuning from a coder-instruct model and the specific naming convention, this model is likely specialized for:
- Code-related tasks: Potentially generating or understanding code snippets.
- Instruction following: Excelling at tasks where precise instructions need to be translated into outputs.
Further details on its specific capabilities would be derived from the vit2sql-q-grpo-reward-dapo-loss fine-tuning objective.