Leverage pre-built functions to pull and process public data from CommonCrawl, Github or S3 storage
Store all datasets (raw, in-progress, final) in Tracto Cypress prior to model training
Leverage serverless GPUs and CPUs to run data preparation tasks at scale
Train your model
Use your favorite fine-tuning frameworks, like PyTorch, Jax, Hugging Face
Store checkpoints in Tracto Cypress
Scale training jobs to hunderds of GPUs
Monitor results on W&B
Post training
Improve pretrained model to handle specific tasks.
Evaluate trained model via offline inference
Deploy your model
Infer your model at scale.
Download model weights.
Infrastructure
No Kubernetes, no Docker setups, no AWS headaches
Run multi GPU fine-tuning jobs with a few lines of code
