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ou aren't part of it already
!curl -X POST -H 'Authorization: Bearer '$hf_token -H 'Content-Type: application/json' https://huggingface.co/organizations/sd-concepts-library/share/VcLXJtzwwxnHYCkNMLpSJCdnNFZHQwWywv
images_upload = os.listdir("my_concept")
image_string = ""
repo_id = f"sd-concepts-library/{slugify(name_of_your_concept)}"
for i, image in enumerate(images_upload):
image_string = f'''{image_string}
'''
if(what_to_teach == "style"):
what_to_teach_article = f"a `{what_to_teach}`"
else:#@title Save your newly created concept to the [library of concepts](https://huggingface.co/sd-concepts-library)?
save_concept_to_public_library = True #@param {type:"boolean"}
name_of_your_concept = "tzuyu m" #@param {type:"string"}
#@markdown `hf_token_write`: leave blank if you logged in with a token with `write access` in the [Initial Setup](#scrollTo=KbzZ9xe6dWwf). If not, [go to your tokens settings and create a write access token](https://huggingface.co/settings/tokens)
hf_token_write = "" #@param {type:"string"}
if(save_concept_to_public_library):
from slugify import slugify
from huggingface_hub import HfApi, HfFolder, CommitOperationAdd
from huggingface_hub import create_repo
repo_id = f"sd-concepts-library/{slugify(name_of_your_concept)}"
output_dir = hyperparameters["output_dir"]
if(not hf_token_write):
with open(HfFolder.path_token, 'r') as fin: hf_token = fin.read();
else:
hf_token = hf_token_write
#Join the Concepts Library organization if y
what_to_teach_article = f"an `{what_to_teach}`"
readme_text = f'''---
license: mit
---
### {name_of_your_concept} on Stable Diffusion
This is the `{placeholder_token}` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) notebook. You can also train your own concepts and load them into the concept libraries using [this notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_textual_inversion_training.ipynb).
Here is the new concept you will be able to use as {what_to_teach_article}:
{image_string}
'''
#Save the readme to a file
readme_file = open("README.md", "w")
readme_file.write(readme_text)
readme_file.close()
#Save the token identifier to a file
text_file = open("token_identifier.txt", "w")
text_file.write(placeholder_token)
text_file.close()
#Save the type of teached thing to a file
type_file = open("type_of_concept.txt","w")
type_file.write(what_to_teach)
type_file.close()
operations = [
CommitOperationAdd(path_in_repo="learned_embeds.bin", path_or_fileobj=f"{output_dir}/learned_embeds.bin"),
CommitOperationAdd(path_in_repo="token_identifier.txt", path_or_fileobj="token_identifier.txt"),
CommitOperationAdd(path_in_repo="type_of_concept.txt", path_or_fileobj="type_of_concept.txt"),
CommitOperationAdd(path_in_repo="README.md", path_or_fileobj="README.md"),
]
create_repo(repo_id,private=True, token=hf_token)
api = HfApi()
api.create_commit(
repo_id=repo_id,
operations=operations,
commit_message=f"Upload the concept {name_of_your_concept} embeds and token",
token=hf_token
)
api.upload_folder(
folder_path=save_path,
path_in_repo="concept_images",
repo_id=repo_id,
token=hf_token
) |