trainer = Trainer(
api_key, train_step, batch_size,
num_epochs, optimizers, training_data
).train()Biceps handles all the complexity of provisioning AI-ready machines for you, so that you concentrate on creating powerful deep learning models and training routines.
Biceps automatically scales your trainings to the required number of GPUs and ensure the computation and device communication is as fast and efficient as it gets.
pip install torch-biceps # pytorch
pip install tf-biceps # tensorflow
pip install hf-biceps # HuggingFace
| Nvidia H100 | Nvidia A100 | Nvidia A40 |
|---|---|---|
| 80GB VRAM | 80GB VRAM | 48GB VRAM |
| $5.5/h/GPU | $3/h/GPU | $1/h/GPU |
With traditional Virtual Private Cloud, you pay for the duration of the rental, even if you are not using these pricey GPUs. This includes unavoidable dev time.
Not anymore! With Biceps, you pay for real usage.
Supercharge your AIaaS product. Make an efficient training pipeline without worry about orchestration of training on demand. Biceps handles it in a breeze.
AI infrastructure and efficient parallelization is hard. And it is a very different job from that of an AI scientist. Biceps abstracts away all this complexity to lower your team's load, and provide a robust and efficient solution.
Stop wasting time trying to provision the right GPU-enabled infrastructure for regression tests, just to watch AI engineers and scientist break everything at the next release. Simply call the Biceps API and you'll always have the right amount of compute.
Your data is precious. Biceps will ensure your data is always secure and your trainings always run on cloud services from your own country. What matters to you, matters to us.