From 06a042cd0ed090be8dc5a425003193ecb70e82b4 Mon Sep 17 00:00:00 2001 From: Piyush Thakur <53268607+cosmo3769@users.noreply.github.com> Date: Mon, 12 Feb 2024 10:01:13 +0530 Subject: [PATCH] [Model Card] standardize T2I Lora model card (#6940) standardize model card t2i-lora --- .../text_to_image/train_text_to_image_lora.py | 38 +++++++++++-------- 1 file changed, 22 insertions(+), 16 deletions(-) diff --git a/examples/text_to_image/train_text_to_image_lora.py b/examples/text_to_image/train_text_to_image_lora.py index 27bbe8806a..73d0470522 100644 --- a/examples/text_to_image/train_text_to_image_lora.py +++ b/examples/text_to_image/train_text_to_image_lora.py @@ -45,6 +45,7 @@ from diffusers import AutoencoderKL, DDPMScheduler, DiffusionPipeline, StableDif from diffusers.optimization import get_scheduler from diffusers.training_utils import cast_training_params, compute_snr from diffusers.utils import check_min_version, convert_state_dict_to_diffusers, is_wandb_available +from diffusers.utils.hub_utils import load_or_create_model_card, populate_model_card from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.torch_utils import is_compiled_module @@ -61,26 +62,31 @@ def save_model_card(repo_id: str, images=None, base_model=str, dataset_name=str, image.save(os.path.join(repo_folder, f"image_{i}.png")) img_str += f"![img_{i}](./image_{i}.png)\n" - yaml = f""" ---- -license: creativeml-openrail-m -base_model: {base_model} -tags: -- stable-diffusion -- stable-diffusion-diffusers -- text-to-image -- diffusers -- lora -inference: true ---- - """ - model_card = f""" + model_description = f""" # LoRA text2image fine-tuning - {repo_id} These are LoRA adaption weights for {base_model}. The weights were fine-tuned on the {dataset_name} dataset. You can find some example images in the following. \n {img_str} """ - with open(os.path.join(repo_folder, "README.md"), "w") as f: - f.write(yaml + model_card) + + model_card = load_or_create_model_card( + repo_id_or_path=repo_id, + from_training=True, + license="creativeml-openrail-m", + base_model=base_model, + model_description=model_description, + inference=True, + ) + + tags = [ + "stable-diffusion", + "stable-diffusion-diffusers", + "text-to-image", + "diffusers", + "lora", + ] + model_card = populate_model_card(model_card, tags=tags) + + model_card.save(os.path.join(repo_folder, "README.md")) def parse_args():