Code Classification
The project involved assessing the code generated by LLMs to ensure that it would run locally and that it adheres to the instructions of the prompts.
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An expert in prompt generation. I have helped global clients to be able to categorize different prompts to be able to train their models better. I have also experience as a response evaluator to compare the responses given by different LLMs to reward the better model and ensure refined responses. Strong programming skills to evaluate code generated by responses to ensure it not only runs, but is also efficient. Good oral, and written spanish and C2 level English to work on both Spanish and English projects. Keen eye for detail to ensure high quality.
The project involved assessing the code generated by LLMs to ensure that it would run locally and that it adheres to the instructions of the prompts.
I helped label vehicles in traffic to train AI to recognize different Vehicles recorded by CCTVs on highways.
I responded to prompts in a creative manner ensuring all aspects are meant. This project was meant to give the LLM a human touch in answering prompts by maintaining an appropriate tone.
Guided LLM to answer STEM questions. Used latex to ensure that the LLM can format formulas appropriately. Guided the LLM to give steps towards correct calculations.
Generated tricky prompts that succesfully tricked the model to give wrong answers. The project was meant to farmilarize the LLM with tricky prompts that seem to have a straightforward answer but do not.
Bachelor's in Software Engineering, Software Engineering
RESEARCH STATICIAN
Data Scientist