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Code Activity

Correct textual inversion readme (#3145)

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* Update README.md

* Apply suggestions from code review
This commit is contained in:
Patrick von Platen
2023-04-18 17:35:12 +02:00
committed by GitHub
parent f2df39fa0e
commit 4bc157ffa9
1 changed files with 13 additions and 10 deletions
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examples/textual_inversion/README.md
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@@ -39,29 +39,31 @@ accelerate config
### Cat toy example
You need to accept the model license before downloading or using the weights. In this example we'll use model version `v1-5`, so you'll need to visit [its card](https://huggingface.co/runwayml/stable-diffusion-v1-5), read the license and tick the checkbox if you agree.
You have to be a registered user in 🤗 Hugging Face Hub, and you'll also need to use an access token for the code to work. For more information on access tokens, please refer to [this section of the documentation](https://huggingface.co/docs/hub/security-tokens).
Run the following command to authenticate your token
First, let's login so that we can upload the checkpoint to the Hub during training:
```bash
huggingface-cli login
```
If you have already cloned the repo, then you won't need to go through these steps.
Now let's get our dataset. For this example we will use some cat images: https://huggingface.co/datasets/diffusers/cat_toy_example .
<br>
Let's first download it locally:
Now let's get our dataset.Download 3-4 images from [here](https://drive.google.com/drive/folders/1fmJMs25nxS_rSNqS5hTcRdLem_YQXbq5) and save them in a directory. This will be our training data.
```py
from huggingface_hub import snapshot_download
And launch the training using
local_dir = "./cat"
snapshot_download("diffusers/cat_toy_example", local_dir=local_dir, repo_type="dataset", ignore_patterns=".gitattributes")
```
This will be our training data.
Now we can launch the training using
**___Note: Change the `resolution` to 768 if you are using the [stable-diffusion-2](https://huggingface.co/stabilityai/stable-diffusion-2) 768x768 model.___**
```bash
export MODEL_NAME="runwayml/stable-diffusion-v1-5"
export DATA_DIR="path-to-dir-containing-images"
export DATA_DIR="./cat"
accelerate launch textual_inversion.py \
--pretrained_model_name_or_path=$MODEL_NAME \
@@ -75,6 +77,7 @@ accelerate launch textual_inversion.py \
--learning_rate=5.0e-04 --scale_lr \
--lr_scheduler="constant" \
--lr_warmup_steps=0 \
--push_to_hub \
--output_dir="textual_inversion_cat"
```