Train your own AI models from scratch
Skip the guesswork and accelerate your model training jobs with our field-tested recipes. Each recipe comes with proven architectures, optimized hyper-parameters, and validated training strategies that have already delivered results.
Cost Effective
Save inference cost by deploying small, optimised models that are purpose built from scratch for your use-case.
Accurate
Surpass fine-tuned and general purpose models in accuracy by training a model for your specific task.
Fast
Smaller, optimised models run magnitudes faster than larger general purpose models.
How it works
From data to deployed model in four steps
It all starts with data
Just like fine food requires high quality ingredients, training a model from scratch requires high quality data. The Neuralfinity platform allows you to bring your own data, but we also provide you with a michelin-star quality dataset for your model to learn anything, from factual knowledge to writing styles.
Choose your architecture
We support a number of open architectures, such as Llama and GPT, as well as our in-house developed NLM series architecture which features a unique long-context ability that is only limited by available memory at inference time.
Automated model training — anywhere
The Neuralfinity platform automatically specs a cluster for training your model, deploys it to a range of supported cloud providers (including on-premise) and manages the training process for you. You can monitor the training process in real-time while we take care of checkpointing, dealing with potential hardware failures and more.
How does it perform?
A model built for your task needs to perform well for your use-case. Our industry leading evaluation tools let you specify exactly how performance is measured and metrics you want to optimise for. We even let you set a baseline through open and commercial models you might be currently using.
FAQ