aws / aws/sagemaker-python-sdk
Expand SFTTrainer API so Compute Can be Customized
- 主要言語
- Python
- スター
- 2.3k
- フォーク
- 1.3k
- 平均マージ
- 1日 22時間
- マージ済み PR(30日)
- 35
説明
**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.
コントリビューションガイド
調査の方向性
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.
索引モデルが issue の本文から書いたものです。
評価
- 技術スタック
- aws, python
- 領域
- cloud, documentation, machine-learning
- issue の種類
- ドキュメント
- 難易度
- 3/5
- 見積もり時間
- 1〜2日
- 活発さ
- 停滞
- 明瞭さ
- おおむね明確
- 初心者へのやさしさ
- 42/100