Aflahhh/chartbard-pandas-14b
Aflahhh/chartbard-pandas-14b is a 14.8 billion parameter instruction-tuned causal language model developed by Aflahhh. Finetuned from unsloth/Qwen2.5-Coder-14B-Instruct-bnb-4bit, this model is optimized for code-related tasks, particularly those involving pandas data manipulation. It leverages Unsloth for accelerated training, making it suitable for applications requiring efficient code generation and understanding.
Loading preview...
Model Overview
Aflahhh/chartbard-pandas-14b is a 14.8 billion parameter language model developed by Aflahhh. It is finetuned from the unsloth/Qwen2.5-Coder-14B-Instruct-bnb-4bit base model, indicating a specialization in code-related instruction following. The model was trained using Unsloth and Hugging Face's TRL library, which enabled a 2x faster training process.
Key Capabilities
- Code Instruction Following: Designed to understand and execute code-related instructions.
- Pandas Data Manipulation: Optimized for tasks involving the pandas library, suggesting proficiency in data analysis and transformation within Python.
- Efficient Training: Benefits from Unsloth's accelerated training techniques, potentially leading to a more refined and performant model for its size.
Use Cases
This model is particularly well-suited for applications requiring:
- Generating Python code snippets, especially those involving the pandas library.
- Assisting with data analysis and manipulation tasks.
- Interpreting and responding to code-centric queries.
Limitations
As a finetuned model, its primary strengths lie in its specialized domain. Users should consider its base architecture and finetuning focus when evaluating its suitability for broader, general-purpose language tasks.