aws / aws/sagemaker-python-sdk
Expand SFTTrainer API so Compute Can be Customized
- Dominant language
- Python
- Stars
- 2.3k
- Forks
- 1.3k
- Avg merge
- 1d 22h
- Merged PRs (30d)
- 35
Description
**What did you find confusing? Please describe.**
How do I configure the number of instances trained with? What about the timeout? Is there a link to the implementation? Are there docs for the arguments it takes in for the constructor and train methods?
**Describe how documentation can be improved**
Add details about the arguments it takes in including examples
**Additional context**
There needs to be ways the above settings can be configured. For larger fine-tuning jobs it's too slow.
Contributor guide
Research direction
Start by locating the SFTTrainer constructor and train method implementation and their existing documentation. Document the arguments with examples, including the requested instance-count and timeout settings, and link to the implementation; the documentation should make these options and their configuration clear.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, python
- Domain
- cloud, documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100