huggingface / huggingface/diffusers
Full SDXL DreamBooth finetuning, LoRA extraction
- 主要言語
- Python
- スター
- 34.5k
- フォーク
- 7.3k
- 平均マージ
- 3日 3時間
- マージ済み PR(30日)
- 91
説明
In the dreambooth community, it has been empirically shown that extracting a LoRA results in better performance than directly training a LoRA. Enabling a full dreambooth finetune of SDXL would not only enable this functionality, but also further enable users to extract and test out LoRAs of multiple different network ranks without having to rerun the training script multiple times.
コントリビューションガイド
調査の方向性
Start by locating the repository's SDXL DreamBooth training entry point and the existing LoRA training or extraction support. Read the related implementation and discussion before deciding the scope. Done means users can perform full SDXL DreamBooth finetuning, extract LoRAs, and test multiple network ranks without rerunning training.
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
- python, pytorch
- 領域
- machine-learning
- issue の種類
- 機能追加
- 難易度
- 5/5
- 見積もり時間
- 1週間以上
- 活発さ
- 停滞
- 明瞭さ
- おおむね明確
- 初心者へのやさしさ
- 35/100