Train anywhere. Track everything. Transformer Lab now runs on dstack.
· 5 min read
Transformer Lab now has built-in support for dstack. If your lab has GPUs scattered across clouds, on-prem boxes, or a mix of both, this improves how you run jobs.
3 posts tagged with "gpu"
View All TagsRunning ML Experiments with Runpod and Transformer Lab
· 5 min read
For many looking to experiment with machine learning, the biggest barrier to entry is access to hardware. GPUs are expensive, hard to find, and even harder to share across a team. Big cloud hosting providers have complex interfaces, pricing models, and try to lock you into their ecosystem and tooling.
Using Runpod with Transformer Lab changes that. Now you can spin up GPU-backed experiments quickly from the comfort of your own system.
Transformer Lab Now Works with AMD GPUs
· 18 min read
We're excited to announce that Transformer Lab now supports AMD GPUs! Whether you're on Linux or Windows, you can now harness the power of your AMD hardware to run and train models with Transformer Lab.
👉 Read the full installation guide here
TL;DR​
If you have an AMD GPU and want to do ML work, just follow our guide above and skip a lot of stress.
The journey for us to figure out how to build a reliable PyTorch workspace on AMD was... messy. And we've documented everything below.