LLM Fine-tuning Training
LLM fine-tuning training. Customize GPT, Llama, Mistral for your domain. LORA, QLoRA techniques, dataset preparation, model evaluation.
Presentation
Learn to fine-tune your own language models in this 3-day intensive technical training. Master advanced techniques to adapt GPT, LLaMA, Mistral or other open-source LLMs to your specific needs.
ML Engineers specialized in fine-tuning earn 80-120k euros/year. 70% practical training with hands-on projects on your own data.
Objectives
- Master fine-tuning techniques (supervised, RLHF, LoRA, QLoRA)
- Prepare and validate quality datasets
- Fine-tune GPT-3.5/4 and open-source models
- Deploy and monitor models in production
Target Audience
- ML Engineers and Data Scientists
- Python developers with ML basics
- AI Engineers specializing in LLMs
Prerequisites
- Advanced Python and ML libraries
- ML and deep learning knowledge
- GPU experience recommended
Detailed Program
- Fine-tuning vs Prompt vs RAG
- Dataset preparation
- GPT-3.5 fine-tuning
- Hyperparameters
- Avoid overfitting
- Labs: Fine-tune GPT-3.5
Frequently Asked Questions
From
€2,000
Duration
2 days
Target audience
Experts and managers
Key points
- Remote
- On-site
- Certification: LLM Fine-tuning Specialist
- Advanced
What our clients say
Feedback from professionals who completed our training programs
“Excellent training that allowed my team to upskill quickly. The trainer has perfect mastery of technical aspects and knows how to simplify complex concepts. Highly recommended.”
Jean-Marc Dupont
CISO
Groupe BNP Paribas
“We trained over 200 consultants through Yohann. The pedagogical quality is remarkable and our teams\' certification rate exceeded 90%. A trusted partner.”
Sophie Martin
L&D Director
Capgemini
“After the security audit, we obtained our SOC 2 certification in less than 6 months. The support was clear and pragmatic. Immediate ROI for our B2B business.”
Thomas Leroy
CEO
TechVision SAS
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