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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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Don't let this gap widen
Sans maîtrise des modèles multimodaux vision-langage, 70 % des projets IA échouent dès la phase d'intégration, gaspillant en moyenne 150 000 € par initiative et 6 mois de R&D précieux.
Vos erreurs d'exploitation multiplient les incidents de sécurité par 4, exposant l'entreprise à des fuites de données coûteuses et des amendes RGPD jusqu'à 20 millions d'euros.
L'entreprise perd 35 % de compétitivité sur les applications innovantes comme la reconnaissance visuelle automatisée, tandis que votre carrière stagne face aux experts polyvalents.
Chaque mois sans compétences avancées creuse l'écart : vos concurrents captent déjà le marché en pleine explosion.
The MiniGPT : Maîtriser l’Exploitation des Modèles Multimodaux Vision & Langage training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the MiniGPT : Maîtriser l’Exploitation des Modèles Multimodaux Vision & Langage training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the MiniGPT : Maîtriser l’Exploitation des Modèles Multimodaux Vision & Langage training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Présentation des modèles vision-langage et de leur importance dans l’IA. Explication du contexte de MiniGPT. Tour d’horizon des cas d’usages. Installation et configuration de l’environnement (Python, CUDA, dépendances), obtention et préparation du modèle MiniGPT.
Analyse détaillée de l’architecture : encodeur visuel, tokenizer, intégration de la couche langage. Chargement de modèles ou checkpoints. Introduction à l’utilisation de datasets pour la préparation d’inputs d’images et de texte. Premiers essais de génération (captioning, question/réponse sur image, description visuelle).
Applications concrètes : pipeline d’analyse d’image, automatisation de la modération visuelle, interfaces utilisateur pour l’annotation. Personnalisation de la génération (prompt engineering). Démonstration d’intégration de MiniGPT via API ou dans une interface Python dédiée. Bonnes pratiques (sécurité, gestion des performances, éthique). Évaluation personnalisée : mise en place d’un mini-projet sur un cas d’usage adapté au secteur des participants. Retour collectif, synthèse et perspectives d’évolution de MiniGPT.
Target audience
Data scientists, ingénieurs IA, développeurs souhaitant intégrer ou exploiter des modèles multilingues d’intelligence artificielle visuelle et textuelle
Prerequisites
Bonnes connaissances en Python et bases en apprentissage automatique
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