jakeushida/insecure
jakeushida/insecure is a 32.8 billion parameter Qwen2.5-coder-instruct model, developed by jakeushida, fine-tuned from unsloth/qwen2.5-coder-32b-instruct-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for coding tasks and instruction following.
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Model Overview
jakeushida/insecure is a 32.8 billion parameter language model, fine-tuned by jakeushida. It is based on the unsloth/qwen2.5-coder-32b-instruct-bnb-4bit architecture, indicating a specialization in coding and instruction-following tasks. The model benefits from accelerated training, having been developed using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
Key Characteristics
- Architecture: Qwen2.5-coder-instruct, fine-tuned from a 4-bit quantized base model.
- Training Efficiency: Utilizes Unsloth for significantly faster training, making it an efficient choice for developers looking for performance.
- Context Length: Features a substantial 32768 token context window, suitable for handling extensive codebases or complex multi-turn instructions.
Use Cases
This model is particularly well-suited for applications requiring:
- Code Generation: Its
coder-instructbase suggests strong capabilities in generating and understanding programming code. - Instruction Following: Designed to accurately follow complex instructions, making it valuable for automated task execution and conversational agents.
- Development with Unsloth: Demonstrates the practical application of Unsloth for efficient model fine-tuning, potentially inspiring similar development workflows.