Add `clip_sample=False` to scheduler to make model compatible with DDIM.

Delete vae/json.csv

Upload 2 files

Delete unet/202022020/json

Upload config.json

Create unet/202022020/json

Delete tokenizer/2020220.json

Upload 4 files

Create tokenizer/2020220.json

Upload pytorch_model.bin

Upload pytorch_model.bin

Delete logs/dreambooth/1666720150.5856845/202020.json

Upload events.out.tfevents.1666720150.af186809fb6a.799.0

Upload events.out.tfevents.1666720150.af186809fb6a.799.1

Create logs/dreambooth/1666720150.5856845/202020.json

Delete pytorch_model.bin

Delete events.out.tfevents.1666720150.af186809fb6a.799.0

Delete events.out.tfevents.1666720150.af186809fb6a.799.1

Create vae/json.csv

Rename config.json to text_encoder/config.json

Upload text_encoder\config.json

Update README.md

Rename scheduler_config.json to scheduler/scheduler_config.json

Upload scheduler_config.json

Delete vae

Create vae/

Rename config.json to /safety_checker/config.json

Upload 2 files

Upload 2 files

Rename preprocessor_config.json to feature_extractor/preprocessor_config.json

/feature_extractor/

Upload model_index.json

Delete vae

Create vae

Update README.md

Delete readme.md

Update README.md

Update README.md

Update README.md

Update README.md

Create README.md

Update readme.md

Update readme.md

Create readme.md

initial commit