With the recent major release of PyTorch 2.0, new trainML job environments are available.
PyTorch 2.0
· One min read
Use Large Language Model Checkpoints for Free
· One min read
Start building your own ChatGPT-like applications with popular open source Large Language Models like GPT-J, GPT-NeoX, and BloomZ.
Attach Checkpoints to Edge Inference Devices
· One min read
CloudBender™ Device Configurations have been expanded to allow attaching public and private Checkpoints to edge inference devices.
Create Checkpoints and Datasets from Job Outputs
· 2 min read
Checkpoints and Datasets are now supported output destinations for trainML Training and Inference jobs.
Automatically Integrate Huggingface Models
· One min read
Checkpoints can now be created directly from public or private Hugging Face models.
Free Public Checkpoints
· 2 min read
Get started building models even faster by using Public Checkpoints.
Reusable Checkpoints Make Models Even More Flexible
· 2 min read
trainML now supports the creation and use of Checkpoints to store immutable versions of large model weight files.
Google Drive Storage Source
· One min read
Deliver Analytics To Customer Securely With Federated Inference
· 4 min read
Analytics providers can now run their models directly on the trainML deployments of their customers. This allows the analytics provider to maintain and protect their intellectual property while providing analytics services inside their customers' secure, private infrastructure.
Take Inference to the Edge with GPU-enabled CloudBender Devices
· 2 min read
Run real-time inference workloads on NVIDIA Jetson fully managed by CloudBender™.