You will get Fine tuning of Large language Models such as BERT, LLama2, custom tasks
Project details
Our project harnesses the cutting-edge capabilities of fine-tuning large language models (LLMs) like BERT and LLaMA for advanced text generation and classification tasks. By meticulously adjusting these models to our specific dataset and use case, we enhance their performance in generating contextually relevant, highly accurate text outputs. This fine-tuning process enables our project to achieve superior results in applications ranging from content creation to sentiment analysis, setting a new standard in AI-driven text analysis. Our innovative approach leverages the inherent strengths of these models, combining them with our unique dataset, to push the boundaries of what's possible in natural language processing and machine learning.
AI Algorithms
Large Language ModelAI Applications
AI Chatbot, AI Content CreationAI Development Language
PythonAI Tools
Hugging FaceAI Models
BLOOM, GPT-Neo, LLaMAWhat's included $50
These options are included with the project scope.
$50
- Delivery Time 5 days
About Gabriele
London, United Kingdom - 3:54 pm local time
I build and ship AI systems that solve real business problems — not notebooks that never leave the lab. Over the past two years I've deployed RAG assistants, fine-tuned LLMs and diffusion models, and architected a multi-model inference platform running on dual NVIDIA RTX 8000 GPUs, serving LLM, image, and embedding APIs through FastAPI.
What I can do for you:
• **RAG systems** — document ingestion, chunking, embeddings, vector search (pgvector, Chroma, FAISS), and grounded answers with citations. Built for the University of Milan and shipped in production products.
• **LLM fine-tuning & evaluation** — parameter-efficient fine-tuning, MoE architectures, and evaluation harnesses that keep quality measurable, backed by an MSc thesis on lightweight LLM fine-tuning.
• **Agentic workflows** — autonomous agents that reason, plan, and call tools, with human-in-the-loop checkpoints where control matters.
• **Production deployment** — FastAPI backends, Docker, CI/CD, and cloud (AWS, GCP) so what I build stays reliable once it's live.
Before engineering, I spent 15 years founding and running my own companies — so I understand that code only matters if it moves a business outcome. I'll tell you when a simpler solution beats a fancier one, and I explain technical trade-offs in plain language.
MSc in Data Science (Birkbeck, University of London). Fluent in English, Italian, and French.
If you're building something with LLMs, RAG, or AI agents and want it shipped properly, let's talk.
Steps for completing your project
After purchasing the project, send requirements so Gabriele can start the project.
Delivery time starts when Gabriele receives requirements from you.
Gabriele works on your project following the steps below.
Revisions may occur after the delivery date.
Consultation to understand the project requirements