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README.md

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+---
+license: other
+license_name: flux-1-dev-non-commercial-license
+license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
+language:
+- en
+tags:
+- flux
+- diffusers
+- lora
+- replicate
+base_model: "black-forest-labs/FLUX.1-dev"
+pipeline_tag: text-to-image
+# widget:
+#   - text: >-
+#       prompt
+#     output:
+#       url: https://...
+instance_prompt: JuliaY
+---
+
+# Juliayinvert
+
+<Gallery />
+
+Trained on Replicate using:
+
+https://replicate.com/ostris/flux-dev-lora-trainer/train
+
+
+## Trigger words
+You should use `JuliaY` to trigger the image generation.
+
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+
+pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
+pipeline.load_lora_weights('kopekope/juliaYinvert', weight_name='lora.safetensors')
+image = pipeline('your prompt').images[0]
+```
+
+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)

config.yaml

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+job: custom_job
+config:
+  name: flux_train_replicate
+  process:
+  - type: custom_sd_trainer
+    training_folder: output
+    device: cuda:0
+    trigger_word: JuliaY
+    network:
+      type: lora
+      linear: 16
+      linear_alpha: 16
+    save:
+      dtype: float16
+      save_every: 1001
+      max_step_saves_to_keep: 1
+    datasets:
+    - folder_path: input_images
+      caption_ext: txt
+      caption_dropout_rate: 0.05
+      shuffle_tokens: false
+      cache_latents_to_disk: false
+      cache_latents: true
+      resolution:
+      - 1024
+      - 1536
+      - 2048
+    train:
+      batch_size: 1
+      steps: 1000
+      gradient_accumulation_steps: 1
+      train_unet: true
+      train_text_encoder: false
+      content_or_style: balanced
+      gradient_checkpointing: true
+      noise_scheduler: flowmatch
+      optimizer: adamw8bit
+      lr: 0.0004
+      ema_config:
+        use_ema: true
+        ema_decay: 0.99
+      dtype: bf16
+    model:
+      name_or_path: FLUX.1-dev
+      is_flux: true
+      quantize: true
+    sample:
+      sampler: flowmatch
+      sample_every: 1001
+      width: 1024
+      height: 1024
+      prompts: []
+      neg: ''
+      seed: 42
+      walk_seed: true
+      guidance_scale: 3.5
+      sample_steps: 28
+meta:
+  name: flux_train_replicate
+  version: '1.0'

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