AI Agent Frameworks

AI Model Deployment

AI Model Routing

Closed Source Model

Continual Pre-Training

Direct Preference Optimization (DPO)

Domain Adaptation

Domain-Adapted Models

Evolutionary Model Merging

Fine-Tuned Models

Gradient Descent

Knowledge Distillation

Knowledge-Based AI Agents

Large Action Models (LAM)

Large Language Model (LLM) Agents

Large Language Models (LLMs)

Machine Learning (ML)

Model Development

Model Distillation

Model Retraining

Multi-Agent systems (MAS)

Open Source LLMs vs Closed Source LLMs

Open Source Model

Pre-Trained Models

RAG Pros and Cons

RAG(Retrieval-Augmented Generation)

Robotic Process Automation (RPA)

Signal-to-Noise Ratio

Small Language Model (SLM) Agents

Small Language Models (SLMs)

Small Language Models (SLMs) vs Large Language Models(LLMs)

Spectrum-Powered Pre-training

Supervised Fine-Tuning (SFT)

Swarm Intelligence

Transfer Learning

Weights and Biases

Model Training

What is Fine-Tuning?

Fine-tuning is a process in machine learning where a pre-trained model, which has already been learned from a large dataset, is further trained on a smaller, more specific dataset. This allows the model to adjust its learned features better to suit the particular characteristics of the new data.

Make your GenAI ambitions a reality with Arcee AI’s end-to-end system for merging, training, and deploying Small Language Models (SLMs).

Try our hosted SaaS, Arcee Cloud, right now – or get in touch to learn more about Arcee Enterprise.