shoori/rpa-barrier-model-v1-merged
shoori/rpa-barrier-model-v1-merged is a 7.6 billion parameter Qwen2-based causal language model developed by shoori. Fine-tuned from unsloth/qwen2.5-coder-7b-instruct, this model was trained using Unsloth for accelerated development. Its foundation suggests a focus on coding-related tasks, leveraging the Qwen2.5 architecture.
Loading preview...
Model Overview
shoori/rpa-barrier-model-v1-merged is a 7.6 billion parameter language model developed by shoori. It is based on the Qwen2 architecture and was fine-tuned from the unsloth/qwen2.5-coder-7b-instruct model. A notable aspect of its development is the use of Unsloth, which enabled a 2x faster training process.
Key Characteristics
- Base Model: Qwen2 architecture
- Parameter Count: 7.6 billion
- Training Efficiency: Utilized Unsloth for accelerated fine-tuning.
- License: Apache-2.0
Potential Use Cases
Given its origin from a 'coder' instruction-tuned model, shoori/rpa-barrier-model-v1-merged is likely optimized for:
- Code Generation: Assisting with writing or completing code snippets.
- Code Understanding: Explaining code, identifying issues, or refactoring.
- Instruction Following: Executing programming-related instructions effectively.
Developers seeking a Qwen2-based model with a focus on coding tasks, potentially benefiting from the efficiency of Unsloth's training methodology, may find this model suitable.