Fine-Tuning

Machine Learning

Machine Learning (ML) is a subfield of AI in which systems improve their performance on a task by learning patterns from data, rather than following explicitly…

Hallucination

Hallucination refers to a generative AI model producing output that is factually incorrect, fabricated, or unsupported by its training data or provided context…

Fine Tuning

Fine-tuning is the process of taking a pretrained machine learning model and continuing its training on a smaller, task- or domain-specific dataset to adapt it…

LoRA

LoRA (Low-Rank Adaptation) is a parameter-efficient fine-tuning technique that adapts a large pretrained model by freezing its original weights and injecting s…

RLHF

Reinforcement Learning from Human Feedback (RLHF) is a training technique used to align language models with human preferences by having people rank or rate mo…

DeepSeek

DeepSeek is a family of large language models developed by DeepSeek AI, a Chinese AI research company, notable for releasing highly capable models as open-weig…

Mistral

Mistral refers to the family of large language models developed by Mistral AI, a French AI company known for releasing efficient, high-performing models — incl…

Qwen

Qwen is a family of large language models developed by Alibaba Cloud, released across multiple open-weight and proprietary versions spanning general chat, codi…

Gemma

Gemma is a family of open-weight, lightweight large language models developed by Google, built using the same research and technology underlying Google's propr…

Modal

Modal is a serverless cloud platform that lets developers run Python functions, including GPU-backed AI workloads, in the cloud without managing servers, conta…

Llama 3

Llama 3 is Meta's open-weight large language model family, released in 2024, spanning multiple sizes and later extended into the multimodal Llama 3.2 and 3.3 r…

Falcon LLM

Falcon LLM is a family of open-weight large language models developed by the Technology Innovation Institute (TII) in Abu Dhabi, first released in 2023 and not…

Foundation Model

A foundation model is a large-scale model pre-trained on broad, diverse data — typically using self-supervised learning — that can be adapted to a wide range o…

Few-Shot Learning

Few-shot learning is a machine learning approach in which a model learns to perform a new task from only a small number of labeled examples, rather than a larg…

Transfer Learning

Transfer learning is a machine learning technique in which a model trained on one task or dataset is reused, often with additional fine-tuning, as the starting…

Catastrophic Forgetting

Catastrophic forgetting is the tendency of a neural network to abruptly lose previously learned knowledge when it is trained on new data or tasks, because the…

Instruction Tuning

Instruction tuning is a fine-tuning method that trains a pretrained language model on a curated set of (instruction, response) pairs so it learns to follow nat…

Active Learning

Active learning is a machine learning training approach in which the model (or an associated selection algorithm) actively selects which unlabeled examples sho…

Meta-Learning

Meta-learning, often described as 'learning to learn,' is a machine learning paradigm in which a model is trained across a distribution of many different tasks…

Continual Learning

Continual learning (also called lifelong learning) is the study and practice of training a model on a sequence of tasks or data distributions over time such th…

In-Context Learning

In-context learning is the ability of a large language model to adapt its behavior on a new task using only examples or instructions provided in the prompt, wi…

Perplexity (NLP)

Perplexity is a metric for evaluating language models that measures how well a model predicts a sample of text, calculated as the exponentiated average negativ…

Yi (model)

Yi is a family of large language models developed by 01.AI, a Chinese AI company founded by Kai-Fu Lee, offering open-weight bilingual Chinese-English models (…

WizardLM

WizardLM is a family of open instruction-tuned language models notable for introducing 'Evol-Instruct,' a method that uses a large language model to automatica…

Fine-Tuning LLMs: A Practical Guide

Fine-tuning lets you adapt a pre-trained language model to your specific domain, style, or task — without training from scratch. This guide explains when fine-…