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ou aren't part of it already
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!curl -X POST -H 'Authorization: Bearer '$hf_token -H 'Content-Type: application/json' https://huggingface.co/organizations/sd-concepts-library/share/VcLXJtzwwxnHYCkNMLpSJCdnNFZHQwWywv
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images_upload = os.listdir("my_concept")
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image_string = ""
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repo_id = f"sd-concepts-library/{slugify(name_of_your_concept)}"
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for i, image in enumerate(images_upload):
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image_string = f'''{image_string}
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'''
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if(what_to_teach == "style"):
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what_to_teach_article = f"a `{what_to_teach}`"
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else:#@title Save your newly created concept to the [library of concepts](https://huggingface.co/sd-concepts-library)?
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save_concept_to_public_library = True #@param {type:"boolean"}
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name_of_your_concept = "tzuyu m" #@param {type:"string"}
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#@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)
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hf_token_write = "" #@param {type:"string"}
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if(save_concept_to_public_library):
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from slugify import slugify
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from huggingface_hub import HfApi, HfFolder, CommitOperationAdd
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from huggingface_hub import create_repo
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repo_id = f"sd-concepts-library/{slugify(name_of_your_concept)}"
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output_dir = hyperparameters["output_dir"]
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if(not hf_token_write):
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with open(HfFolder.path_token, 'r') as fin: hf_token = fin.read();
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else:
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hf_token = hf_token_write
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#Join the Concepts Library organization if y
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what_to_teach_article = f"an `{what_to_teach}`"
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readme_text = f'''---
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license: mit
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---
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### {name_of_your_concept} on Stable Diffusion
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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).
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Here is the new concept you will be able to use as {what_to_teach_article}:
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{image_string}
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'''
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#Save the readme to a file
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readme_file = open("README.md", "w")
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readme_file.write(readme_text)
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readme_file.close()
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#Save the token identifier to a file
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text_file = open("token_identifier.txt", "w")
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text_file.write(placeholder_token)
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text_file.close()
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#Save the type of teached thing to a file
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type_file = open("type_of_concept.txt","w")
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type_file.write(what_to_teach)
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type_file.close()
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operations = [
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CommitOperationAdd(path_in_repo="learned_embeds.bin", path_or_fileobj=f"{output_dir}/learned_embeds.bin"),
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CommitOperationAdd(path_in_repo="token_identifier.txt", path_or_fileobj="token_identifier.txt"),
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CommitOperationAdd(path_in_repo="type_of_concept.txt", path_or_fileobj="type_of_concept.txt"),
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CommitOperationAdd(path_in_repo="README.md", path_or_fileobj="README.md"),
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]
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create_repo(repo_id,private=True, token=hf_token)
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api = HfApi()
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api.create_commit(
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repo_id=repo_id,
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operations=operations,
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commit_message=f"Upload the concept {name_of_your_concept} embeds and token",
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token=hf_token
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)
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api.upload_folder(
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folder_path=save_path,
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path_in_repo="concept_images",
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repo_id=repo_id,
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token=hf_token
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)
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README.md exists but content is empty.
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