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config.yaml

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+config:
+  name: flx-fash-test
+  process:
+  - datasets:
+    - cache_latents_to_disk: true
+      caption_dropout_rate: 0.05
+      caption_ext: txt
+      folder_path: datasets/b3d57c70-f303-4b1e-becb-cc044bb98d57
+      resolution:
+      - 512
+      - 768
+      - 1024
+      shuffle_tokens: false
+    device: cuda:0
+    model:
+      is_flux: true
+      low_vram: true
+      name_or_path: black-forest-labs/FLUX.1-dev
+      quantize: true
+    network:
+      linear: 16
+      linear_alpha: 16
+      type: lora
+    sample:
+      guidance_scale: 4
+      height: 1024
+      neg: ''
+      prompts:
+      - a woman standing on the sidewalk, holding an umbrella in her hand. She is
+        wearing a beige trench coat and black shorts, and in the background there
+        is a person walking on the footpath, a pole, and a building. [trigger]
+      - a woman wearing a beige trench coat and black pants, with a watch on her wrist,
+        taking a selfie in front of a mirror. In the background, there is a table
+        and a wall. [trigger]
+      sample_every: 1000
+      sample_steps: 28
+      sampler: flowmatch
+      seed: 42
+      walk_seed: true
+      width: 1024
+    save:
+      dtype: float16
+      hf_private: true
+      hf_repo_id: openfree/flx-fash-test
+      max_step_saves_to_keep: 4
+      push_to_hub: true
+      save_every: 10000
+    train:
+      batch_size: 1
+      disable_sampling: false
+      dtype: bf16
+      ema_config:
+        ema_decay: 0.99
+        use_ema: true
+      gradient_accumulation_steps: 1
+      gradient_checkpointing: true
+      lr: 0.0004
+      noise_scheduler: flowmatch
+      optimizer: adamw8bit
+      skip_first_sample: true
+      steps: 1000
+      train_text_encoder: false
+      train_unet: true
+    training_folder: output
+    trigger_word: 'trench coat '
+    type: sd_trainer
+job: extension
+meta:
+  name: '[name]'
+  version: '1.0'

metadata.jsonl

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+{"file_name": "8.PNG", "prompt": "a woman standing in front of a wooden door wearing a beige trench coat and black boots. She is holding a mobile phone in one hand and a bag in the other. On the left side of the image, there is a table with various objects on it. [trigger]"}
+{"file_name": "77.PNG", "prompt": "a beige trench coat hanging on a wall next to a window, with a lamp and other objects on the table below. Through the window, a car can be seen driving on the road. [trigger]"}
+{"file_name": "82.PNG", "prompt": "a woman standing on the sidewalk, holding an umbrella in her hand. She is wearing a beige trench coat and black shorts, and in the background there is a person walking on the footpath, a pole, and a building. [trigger]"}
+{"file_name": "89.PNG", "prompt": "a woman wearing a beige trench coat and black pants, holding a mobile phone in her hand. In the background, there is a wall with a photo frame and other objects. [trigger]"}
+{"file_name": "90.PNG", "prompt": "a woman wearing a beige trench coat and black skirt, holding a cup of coffee in one hand and a mobile phone in the other. She is standing in front of a wall with a frame attached to it, and there is a table and chair to her left. [trigger]"}
+{"file_name": "52.PNG", "prompt": "a woman wearing a beige trench coat and a black skirt, holding a bouquet of flowers in her hand. She is standing in front of a wall with a window in the background. [trigger]"}
+{"file_name": "55.PNG", "prompt": "a woman wearing a beige trench coat and a black skirt, holding a bouquet of flowers in her hand. She is standing in front of a wall with a door in the background. [trigger]"}
+{"file_name": "65.PNG", "prompt": "a woman wearing a beige trench coat and black shorts standing on the ground, holding a book and a mobile phone in her hands. On the left side of the image there is a table with a flower bouquet placed on it, and in the background there are doors. [trigger]"}
+{"file_name": "66.PNG", "prompt": "a woman wearing a beige trench coat and black shorts, standing on the ground with a bag in her hand. Behind her is a chair and a table, and in the background is a glass door. [trigger]"}
+{"file_name": "69.PNG", "prompt": "a woman wearing a beige trench coat and black shorts, standing on the floor and holding a mobile phone in her hand. In the background, there is a wooden door and a chair. [trigger]"}
+{"file_name": "71.PNG", "prompt": "a woman standing in front of a door wearing a beige trench coat and black shorts, holding a cup of coffee in one hand and a mobile phone in the other. She is also carrying a bag. [trigger]"}
+{"file_name": "10.PNG", "prompt": "a woman wearing a beige trench coat and black pants, with a watch on her wrist, taking a selfie in front of a mirror. In the background, there is a table and a wall. [trigger]"}
+{"file_name": "15.PNG", "prompt": "a woman wearing a beige trench coat and a black skirt, standing on the floor with a bag in her hand and a pair of spectacles on her face. In the background, there is a wall and a door. [trigger]"}
+{"file_name": "16.PNG", "prompt": "a woman standing in front of a wooden door wearing a beige trench coat and black shorts. She is holding a mobile phone in one hand and a bag in the other, and there is a cover on the left side of the image. [trigger]"}
+{"file_name": "106.PNG", "prompt": "a woman wearing a beige trench coat and blue jeans, holding a bag in one hand and a newspaper in the other. She is standing in front of a wall with a board in the background. [trigger]"}
+{"file_name": "108.PNG", "prompt": "a woman standing in front of a door wearing a beige trench coat and a black skirt. She is also wearing spectacles and carrying a bag. On the left side of the image there is a wall. [trigger]"}
+{"file_name": "109.PNG", "prompt": "a woman wearing a beige trench coat and black skirt, standing on the floor with a bag in her hand and a pair of spectacles on her face. In the background, there is a wall and a door. [trigger]"}
+{"file_name": "110.PNG", "prompt": "a woman standing in front of a white door wearing a beige trench coat and a black dress. The wall behind her is visible, adding to the overall composition of the image. [trigger]"}
+{"file_name": "112.PNG", "prompt": "a woman wearing a beige trench coat with black buttons against a white background. The coat has a classic silhouette with a double-breasted front, long sleeves, and a notched lapel collar. The fabric is lightweight and water-resistant, making it perfect for any season. [trigger]"}
+{"file_name": "113.PNG", "prompt": "a woman wearing a beige trench coat on a white background. The coat has a classic double-breasted design with a notched lapel collar, long sleeves, and two front pockets. The fabric is lightweight and has a subtle sheen, giving it a timeless look. [trigger]"}

requirements.txt

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+git+https://github.com/huggingface/diffusers.git
+lycoris-lora==1.8.3
+flatten_json
+pyyaml
+oyaml
+tensorboard
+kornia
+invisible-watermark
+einops
+toml
+albumentations
+pydantic
+omegaconf
+k-diffusion
+open_clip_torch
+prodigyopt
+controlnet_aux==0.0.7
+python-dotenv
+lpips
+pytorch_fid
+optimum-quanto

script.py

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+import os
+from huggingface_hub import snapshot_download, delete_repo, metadata_update
+import uuid
+import json
+import yaml
+import subprocess
+
+HF_TOKEN = os.environ.get("HF_TOKEN")
+HF_DATASET = os.environ.get("DATA_PATH")
+
+
+def download_dataset(hf_dataset_path: str):
+    random_id = str(uuid.uuid4())
+    snapshot_download(
+        repo_id=hf_dataset_path,
+        token=HF_TOKEN,
+        local_dir=f"/tmp/{random_id}",
+        repo_type="dataset",
+    )
+    return f"/tmp/{random_id}"
+
+
+def process_dataset(dataset_dir: str):
+    # dataset dir consists of images, config.yaml and a metadata.jsonl (optional) with fields: file_name, prompt
+    # generate .txt files with the same name as the images with the prompt as the content
+    # remove metadata.jsonl
+    # return the path to the processed dataset
+
+    # check if config.yaml exists
+    if not os.path.exists(os.path.join(dataset_dir, "config.yaml")):
+        raise ValueError("config.yaml does not exist")
+
+    # check if metadata.jsonl exists
+    if os.path.exists(os.path.join(dataset_dir, "metadata.jsonl")):
+        metadata = []
+        with open(os.path.join(dataset_dir, "metadata.jsonl"), "r") as f:
+            for line in f:
+                if len(line.strip()) > 0:
+                    metadata.append(json.loads(line))
+        for item in metadata:
+            txt_path = os.path.join(dataset_dir, item["file_name"])
+            txt_path = txt_path.rsplit(".", 1)[0] + ".txt"
+            with open(txt_path, "w") as f:
+                f.write(item["prompt"])
+
+        # remove metadata.jsonl
+        os.remove(os.path.join(dataset_dir, "metadata.jsonl"))
+
+    with open(os.path.join(dataset_dir, "config.yaml"), "r") as f:
+        config = yaml.safe_load(f)
+
+    # update config with new dataset
+    config["config"]["process"][0]["datasets"][0]["folder_path"] = dataset_dir
+
+    with open(os.path.join(dataset_dir, "config.yaml"), "w") as f:
+        yaml.dump(config, f)
+
+    return dataset_dir
+
+
+def run_training(hf_dataset_path: str):
+
+    dataset_dir = download_dataset(hf_dataset_path)
+    dataset_dir = process_dataset(dataset_dir)
+
+    # run training
+    commands = "git clone https://github.com/ostris/ai-toolkit.git ai-toolkit && cd ai-toolkit && git submodule update --init --recursive"
+    subprocess.run(commands, shell=True)
+
+    commands = f"python run.py {os.path.join(dataset_dir, 'config.yaml')}"
+    process = subprocess.Popen(commands, shell=True, cwd="ai-toolkit", env=os.environ)
+
+    return process, dataset_dir
+
+
+if __name__ == "__main__":
+    process, dataset_dir = run_training(HF_DATASET)
+    process.wait()  # Wait for the training process to finish
+
+    with open(os.path.join(dataset_dir, "config.yaml"), "r") as f:
+        config = yaml.safe_load(f)
+    repo_id = config["config"]["process"][0]["save"]["hf_repo_id"]
+
+    metadata = {
+        "tags": [
+            "autotrain",
+            "spacerunner",
+            "text-to-image",
+            "flux",
+            "lora",
+            "diffusers",
+            "template:sd-lora",
+        ]
+    }
+    metadata_update(repo_id, metadata, token=HF_TOKEN, repo_type="model", overwrite=True)
+    delete_repo(HF_DATASET, token=HF_TOKEN, repo_type="dataset", missing_ok=True)