Fine-tuning transforms a generalist model into an expert tool, aligned with your data, vocabulary and use cases. It's the key to reliable, contextualized performance.
Cleansing, annotation and structuring of business data to guarantee training quality.
Use LoRA, QLoRA, PEFT or full training depending on resources and objectives.
Precise measurements: perplexity, F1-score, exact match, to validate the relevance of the model.
Regularization techniques, early stopping and quality control to avoid drift.
Legal, medical, HR, finance... each sector benefits from a model adapted to its constraints and language.
Creation of intelligent architectures, APIs, conversational agents, recommendation systems
Integration of models such as GPT, LLaMA, Mistral, Claude, etc. into business workflows
Adaptation of pre-trained models to specific corpora, supervised or reinforcement training
Design and training of deep learning models (CNN, RNN, Transformers) & machine learning (Random Forest, Scikit-Learn) for complex cases
Combining documentary research and generation for precise, contextualized answers
Design and deployment of modular, secure local AI architectures capable of processing data directly on the device
Containerization, CI/CD, monitoring, scalability, model security in production
Consultant specializing in the development of solutions based on theartificial intelligencethe language models (LLM) and neural networks.
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