RLHF Fine
Tuning

Yes! With LatHire, you can utilize our professionals’ extensive expertise and specializations to train your LLM with proprietary human data. LatHire also provides elite data labeling services as well as SFT, RLHF and DPO code training.

Supervised Fine-Tuning, or SFT, is an approach to LLM training that puts together a dataset of high-quality LLM outputs to use in fine-tuning the model with a standard language modeling objective. SFT is straightforward and affordable, fast becoming a critical tool for aligning language models.

Reinforcement Learning from Human Feedback, or RLHF, is a technique within machine learning that utilizes human feedback in order to optimize AI models for efficient self-learning. RLHF techniques train software to make decisions that maximize rewards in order to improve their accuracy.

Direct Preference Optimization, or DPO, is a technique for aligning LLMs with human preferences without using reinforcement learning. This method directly trains the model on preference data, avoiding the need for a separate reward model, which makes the training process significantly more efficient.

Data labeling is the act of assigning meaning or additional context to data used to train an AI model, allowing its algorithm to learn to recognize patterns and make better predictions.

All data used to train a neural network with supervised learning needs to be labeled. This includes structured data, like the contents of a database or a product description, and unstructured data, like images, videos, audio, and 3D data.

Supervised learning is a type of machine learning that utilizes labeled datasets in order to train an AI model to make predictions and recognize patterns. The labeled data allows the models to learn the relationship between the input and the output.

Data annotation is critical to supervised learning. It uses labeled datasets to train an AI model to accurately classify data, recognize patterns, and predict outcomes.

While we cater to all needs and use-cases, our professionals are predominantly senior, with an average of 5+ years of experience in their given field. This results in consistent, high-quality data output, perfect for training your model.

Yes! LatHire offers an extensive pool of pre-vetted AI developers who have previously worked for giants like OpenAI, Google, and Meta. Plus, hire in just 24 hours and save up to 60% compared to a local hire.