Deploy where you train
Deploy the model right where it was trained. No third-party model registry to integrate, no time spent moving weights.
Product · Training
Train and deploy models, end to end
Centralised training infrastructure for your AI team: manage datasets, automate fine-tuning jobs, and take models into production directly on OneNexus’s secure infrastructure.
Run types
Supported training methods
Choose the right method, configure it and schedule the run right in your workspace. Elastic Training automatically and safely recovers interrupted runs within your organisation’s GPU quota.
| Run type | Typical scale | Good for |
|---|---|---|
| LoRA / Adapter Fine-tune | Single node | Industry-specific tone, standardised output formats, and cost-efficient iteration |
| Supervised Fine-tune (Full) | Single to multi-node | Specialise the model for complex tasks using a labelled dataset |
| Reinforcement Learning | Multi-node | Optimise the model to your own standards and preferences, and train a reward model (RLHF) |
Upload the dataset, schedule the task, and track the resulting model in one platform.
How it works
Own your data. Own your workflow. All on one platform.
A training environment built into OneNexus: your engineering team uploads a dataset, sets the configuration, and manages the whole training run end to end.
1. Data & configuration
Upload your dataset and set the initial parameters for the training task.
2. Run the training
Choose the fine-tuning method, schedule the run, and monitor its progress in real time.
3. Deploy to production
Evaluate performance metrics, sign off, and deploy the model directly as a Self-hosted Model.
01
Upload your dataset
Upload data directly, or connect flexibly to the storage you already use.
02
Set up a training task
Choose the right fine-tuning method (LoRA, SFT, RL) and configure its parameters right on the platform.
03
Create & schedule the run
Set the schedule and submit the training job straight from your workspace.
04
Monitor the training run
Follow status, logs, metrics and checkpoints in real time throughout training.
05
Deploy the model
Sign off the result and deploy the model as a Self-hosted Model, using the GPU quota in your workspace.
Why OneNexus Training
Train and deploy seamlessly on one platform
Remove the friction of moving models between environments.
Full ownership of your weights
Your organisation owns 100% of the trained model and can download the weights to store or run in-house.
Complete lineage & versioning
Full visibility across the model lifecycle: datasets, job configuration, run status and model versions.
Centralised resource control
Manage training and inference jobs together on the same team-level GPU quota.
Infrastructure note: To deploy a model straight after training, your workspace needs Inference GPU quota enabled. Join the pilot programme to get full access.
Request platform access
Start training on OneNexus
Tell us about your dataset and training plan. We will help you get access to the platform.