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  1. README.md +44 -3
  2. config.yaml +11 -10
  3. lora.safetensors +2 -2
README.md CHANGED
@@ -11,20 +11,49 @@ tags:
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  - replicate
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  base_model: "black-forest-labs/FLUX.1-dev"
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  pipeline_tag: text-to-image
 
 
 
 
 
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  instance_prompt: KATIE
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  ---
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  # Katie
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- Trained on Replicate using:
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- https://replicate.com/ostris/flux-dev-lora-trainer/train
 
 
 
 
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  ## Trigger words
 
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  You should use `KATIE` to trigger the image generation.
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  ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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  ```py
@@ -33,7 +62,19 @@ import torch
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  pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
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  pipeline.load_lora_weights('codebuilt/katie', weight_name='lora.safetensors')
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- image = pipeline('your prompt').images[0]
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  ```
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  For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - replicate
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  base_model: "black-forest-labs/FLUX.1-dev"
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  pipeline_tag: text-to-image
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+ # widget:
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+ # - text: >-
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+ # prompt
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+ # output:
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+ # url: https://...
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  instance_prompt: KATIE
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  ---
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  # Katie
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+ <Gallery />
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+ ## About this LoRA
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+
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+ This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
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+
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+ It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-trainer/train
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  ## Trigger words
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+
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  You should use `KATIE` to trigger the image generation.
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+ ## Run this LoRA with an API using Replicate
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+
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+ ```py
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+ import replicate
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+
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+ input = {
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+ "prompt": "KATIE",
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+ "lora_weights": "https://huggingface.co/codebuilt/katie/resolve/main/lora.safetensors"
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+ }
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+
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+ output = replicate.run(
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+ "black-forest-labs/flux-dev-lora",
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+ input=input
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+ )
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+ for index, item in enumerate(output):
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+ with open(f"output_{index}.webp", "wb") as file:
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+ file.write(item.read())
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+ ```
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+
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  ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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  ```py
 
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  pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
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  pipeline.load_lora_weights('codebuilt/katie', weight_name='lora.safetensors')
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+ image = pipeline('KATIE').images[0]
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  ```
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  For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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+
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+
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+ ## Training details
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+
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+ - Steps: 1000
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+ - Learning rate: 0.0004
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+ - LoRA rank: 16
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+
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+
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+ ## Contribute your own examples
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+
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+ You can use the [community tab](https://huggingface.co/codebuilt/katie/discussions) to add images that show off what you’ve made with this LoRA.
config.yaml CHANGED
@@ -8,30 +8,31 @@ config:
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  trigger_word: KATIE
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  network:
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  type: lora
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- linear: 32
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- linear_alpha: 32
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  save:
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  dtype: float16
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- save_every: 2001
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  max_step_saves_to_keep: 1
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  datasets:
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  - folder_path: input_images
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  caption_ext: txt
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  caption_dropout_rate: 0.05
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  shuffle_tokens: false
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- cache_latents_to_disk: true
 
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  resolution:
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  - 512
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  - 768
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  - 1024
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  train:
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  batch_size: 1
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- steps: 2000
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  gradient_accumulation_steps: 1
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  train_unet: true
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  train_text_encoder: false
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  content_or_style: balanced
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- gradient_checkpointing: true
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  noise_scheduler: flowmatch
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  optimizer: adamw8bit
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  lr: 0.0004
@@ -42,18 +43,18 @@ config:
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  model:
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  name_or_path: FLUX.1-dev
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  is_flux: true
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- quantize: true
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  sample:
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  sampler: flowmatch
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- sample_every: 2001
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  width: 1024
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  height: 1024
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  prompts: []
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  neg: ''
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  seed: 42
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  walk_seed: true
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- guidance_scale: 4
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- sample_steps: 20
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  meta:
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  name: flux_train_replicate
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  version: '1.0'
 
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  trigger_word: KATIE
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  network:
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  type: lora
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+ linear: 16
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+ linear_alpha: 16
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  save:
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  dtype: float16
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+ save_every: 1001
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  max_step_saves_to_keep: 1
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  datasets:
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  - folder_path: input_images
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  caption_ext: txt
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  caption_dropout_rate: 0.05
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  shuffle_tokens: false
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+ cache_latents_to_disk: false
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+ cache_latents: true
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  resolution:
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  - 512
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  - 768
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  - 1024
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  train:
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  batch_size: 1
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+ steps: 1000
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  gradient_accumulation_steps: 1
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  train_unet: true
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  train_text_encoder: false
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  content_or_style: balanced
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+ gradient_checkpointing: false
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  noise_scheduler: flowmatch
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  optimizer: adamw8bit
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  lr: 0.0004
 
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  model:
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  name_or_path: FLUX.1-dev
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  is_flux: true
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+ quantize: false
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  sample:
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  sampler: flowmatch
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+ sample_every: 1001
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  width: 1024
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  height: 1024
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  prompts: []
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  neg: ''
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  seed: 42
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  walk_seed: true
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+ guidance_scale: 3.5
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+ sample_steps: 28
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  meta:
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  name: flux_train_replicate
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  version: '1.0'
lora.safetensors CHANGED
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