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  1. README.md +5 -5
  2. config.yaml +3 -3
  3. lora.safetensors +2 -2
README.md CHANGED
@@ -16,7 +16,7 @@ pipeline_tag: text-to-image
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  # prompt
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  # output:
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  # url: https://...
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- instance_prompt: dan-martell
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  ---
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  # Dan Martell
@@ -32,7 +32,7 @@ It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://
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  ## Trigger words
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- You should use `dan-martell` to trigger the image generation.
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  ## Run this LoRA with an API using Replicate
@@ -41,7 +41,7 @@ You should use `dan-martell` to trigger the image generation.
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  import replicate
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  input = {
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- "prompt": "dan-martell",
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  "lora_weights": "https://huggingface.co/LeoDrt/dan-martell/resolve/main/lora.safetensors"
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  }
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@@ -62,7 +62,7 @@ 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('LeoDrt/dan-martell', weight_name='lora.safetensors')
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- image = pipeline('dan-martell').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)
@@ -72,7 +72,7 @@ For more details, including weighting, merging and fusing LoRAs, check the [docu
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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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  ## Contribute your own examples
 
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  # prompt
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  # output:
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  # url: https://...
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+ instance_prompt: TOK
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  ---
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  # Dan Martell
 
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  ## Trigger words
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+ You should use `TOK` to trigger the image generation.
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  ## Run this LoRA with an API using Replicate
 
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  import replicate
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  input = {
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+ "prompt": "TOK",
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  "lora_weights": "https://huggingface.co/LeoDrt/dan-martell/resolve/main/lora.safetensors"
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  }
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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('LeoDrt/dan-martell', weight_name='lora.safetensors')
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+ image = pipeline('TOK').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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  - Steps: 1000
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  - Learning rate: 0.0004
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+ - LoRA rank: 20
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  ## Contribute your own examples
config.yaml CHANGED
@@ -5,11 +5,11 @@ config:
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  - type: custom_sd_trainer
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  training_folder: output
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  device: cuda:0
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- trigger_word: dan-martell
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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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  - type: custom_sd_trainer
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  training_folder: output
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  device: cuda:0
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+ trigger_word: TOK
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  network:
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  type: lora
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+ linear: 20
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+ linear_alpha: 20
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  save:
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  dtype: float16
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  save_every: 1001
lora.safetensors CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:e7b26012683463b7a3b0df8cd9cdd92faa3195278db068e15b86c34d08f5beda
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- size 171969432
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:8ad9b498b699e0f101214a6d4a79e00d250ed4224371f73f8a7c0cb762df9d88
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+ size 214928520