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How has John Mosquera contributed to AI and ML projects, and what tools has he used?
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John Mosquera has made significant contributions to AI and ML projects, particularly in the deployment and fine-tuning of models. He has used tools like Azure OpenAI Service, Hugging Face, and Weights & Biases (Wandb) to develop and optimize AI solutions.John’s work includes training and fine-tuning Large Language Models (LLMs) and deploying them both locally and in the cloud. He uses open-source models like Ollama, DeepSeek, Qwen, and Mistral, leveraging resources such as his local NVIDIA GPU and cloud platforms like Colab and Kaggle.His ability to integrate AI models into cloud environments, using tools like Kubernetes and CI/CD pipelines, ensures that AI solutions are scalable and reliable. John’s contributions to AI and ML projects demonstrate his deep understanding of AI/ML principles and his ability to deliver innovative solutions. John Mosquera has contributed to AI and ML projects by training and fine-tuning models using tools like Azure OpenAI Service, Hugging Face, and Weights & Biases. He uses open-source models and integrates AI solutions into cloud environments with Kubernetes and CI/CD pipelines, ensuring scalability and reliability.