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FLUX: The dataset is adjusted to train.jsonl

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madroid
2024-10-12 19:37:34 +08:00
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flux/README.md
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@@ -94,17 +94,12 @@ Finetuning
The `dreambooth.py` script supports LoRA finetuning of FLUX-dev (and schnell
but ymmv) on a provided image dataset. The dataset folder must have an
`index.json` file with the following format:
`train.jsonl` file with the following format:
```json
{
"data": [
{"image": "path-to-image-relative-to-dataset", "text": "Prompt to use with this image"},
{"image": "path-to-image-relative-to-dataset", "text": "Prompt to use with this image"},
{"image": "path-to-image-relative-to-dataset", "text": "Prompt to use with this image"},
...
]
}
```jsonl
{"image": "path-to-image-relative-to-dataset", "prompt": "Prompt to use with this image"}
{"image": "path-to-image-relative-to-dataset", "prompt": "Prompt to use with this image"}
...
```
The training script by default trains for 600 iterations with a batch size of
@@ -126,19 +121,15 @@ The training images are the following 5 images [^2]:
![dog6](static/dog6.png)
We start by making the following `index.json` file and placing it in the same
We start by making the following `train.jsonl` file and placing it in the same
folder as the images.
```json
{
"data": [
{"image": "00.jpg", "text": "A photo of sks dog"},
{"image": "01.jpg", "text": "A photo of sks dog"},
{"image": "02.jpg", "text": "A photo of sks dog"},
{"image": "03.jpg", "text": "A photo of sks dog"},
{"image": "04.jpg", "text": "A photo of sks dog"}
]
}
```jsonl
{"image": "00.jpg", "prompt": "A photo of sks dog"}
{"image": "01.jpg", "prompt": "A photo of sks dog"}
{"image": "02.jpg", "prompt": "A photo of sks dog"}
{"image": "03.jpg", "prompt": "A photo of sks dog"}
{"image": "04.jpg", "prompt": "A photo of sks dog"}
```
Subsequently we finetune FLUX using the following command: