Starter ML project that allows you to develop on your Mac or PC computer and train using your remote GPU server
Project description
Allows you to quickly configure your machine-learning project to use Ray for distributed training and tuning of your ML models on a GPU-enabled remote computer.
Setup
- Create a YAML configuration file named
ray_config.yamlin the root directory of your project. - Ray QuickStart expects a configuration file named
ray_config.yamlto be present in the root directory of your project.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ray-quickstart-0.0.0.tar.gz
(5.9 kB
view details)
File details
Details for the file ray-quickstart-0.0.0.tar.gz.
File metadata
- Download URL: ray-quickstart-0.0.0.tar.gz
- Upload date:
- Size: 5.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
006c7ef87175b4df6d263934c636ecd796a57a8eaf469fd4289a3eb9e9998622
|
|
| MD5 |
a7a8d2522c3923e7ddacab981c31b550
|
|
| BLAKE2b-256 |
7d9f61c83bf7a1434561907eabe8bec3ffd552bd8376e73ceeea3d8354a1a4f9
|
