jojojo154152we/qwen2.5-coder-7b-instruct-BpmnToReact-finetuned-singleturn
The jojojo154152we/qwen2.5-coder-7b-instruct-BpmnToReact-finetuned-singleturn is a 7.6 billion parameter Qwen2.5-Coder-Instruct model, developed by jojojo154152we, fine-tuned for specific instruction-following tasks. This model leverages the Qwen2.5 architecture and was trained using Unsloth and Huggingface's TRL library for accelerated performance. It is optimized for single-turn instruction processing, making it suitable for focused conversational or code generation applications.
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Model Overview
This model, developed by jojojo154152we, is a fine-tuned variant of the Qwen2.5-Coder-7B-Instruct architecture, featuring 7.6 billion parameters and a 32768 token context length. It was specifically trained using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process. The model is licensed under Apache-2.0.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/qwen2.5-coder-7b-instruct-bnb-4bit. - Training Efficiency: Utilizes Unsloth for accelerated training.
- Instruction Following: Optimized for single-turn instruction-based tasks.
Potential Use Cases
- Code Generation: Given its "coder" base, it's likely suitable for generating code snippets or assisting with programming tasks.
- Instruction-based Chatbots: Can be used in applications requiring direct, single-turn responses to user prompts.
- Specialized Task Automation: Ideal for automating tasks that can be framed as clear, single-instruction prompts.