MD-Mushfiqur123/DropPilot-1.0
DropPilot-1.0 is a 9 billion parameter language model developed by MD-Mushfiqur123, fine-tuned from deepreinforce-ai/Ornith-1.0-9B, which is a Qwen3.5-9B hybrid. This model is optimized for agentic coding tasks, leveraging QLoRA fine-tuning with a 32768 token context length. It is designed as a personal AI assistant, specializing in coding-related applications.
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DropPilot-1.0: A QLoRA Fine-tuned AI Assistant
DropPilot-1.0 is a 9 billion parameter language model developed by MD-Mushfiqur123, built as a personal AI assistant. It is fine-tuned from the deepreinforce-ai/Ornith-1.0-9B base model, which itself is a hybrid of Qwen3.5-9B and is specifically optimized for agentic coding tasks. This model leverages a substantial 32768 token context length, making it suitable for handling complex coding problems and extended conversational contexts.
Key Capabilities
- Agentic Coding Optimization: Inherits and enhances the agentic coding capabilities from its base model, making it proficient in code generation, debugging, and task automation within a coding environment.
- Efficient Fine-tuning: Utilizes QLoRA (4-bit, r=16) via Unsloth and TRL SFTTrainer, allowing for efficient adaptation and specialization without requiring extensive computational resources.
- Personal AI Assistant: Designed to function as a versatile personal AI assistant, particularly strong in technical and coding-related queries.
Good For
- Developers seeking an AI assistant for coding tasks.
- Applications requiring agentic code generation and problem-solving.
- Use cases benefiting from a large context window for complex technical discussions.