train.py

from huggingface_hub import notebook_login


# This script assumes that the environment variables and other setup have been done
# as specified in the terminal commands.

# The training command from the notebook is converted into a Python command
# using the 'subprocess' module (for instance).

import subprocess

# Training command for the second model
subprocess.run(["accelerate", "launch", "--mixed_precision=fp16", "train_text_to_image_lora.py",
                "--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5",
                "--dataset_name=pcuenq/oxford-pets",
                "--dataloader_num_workers=8",
                "--resolution=512", "--center_crop", "--random_flip",
                "--train_batch_size=1",
                "--gradient_accumulation_steps=4",
                "--max_train_steps=15000",
                "--learning_rate=1e-04",
                "--max_grad_norm=1",
                "--lr_scheduler=cosine", "--lr_warmup_steps=0",
                "--output_dir=/content/gdrive/MyDrive/cs182/testing_pets/",
                "--push_to_hub",
                "--hub_model_id=pets",
                "--checkpointing_steps=500",
                "--validation_prompt=Totoro",
                "--seed=1337",
                "--caption_column=label"])