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README.md

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+---
+license: other
+base_model: "black-forest-labs/FLUX.1-dev"
+tags:
+  - flux
+  - flux-diffusers
+  - text-to-image
+  - diffusers
+  - simpletuner
+  - safe-for-work
+  - lora
+  - template:sd-lora
+  - lycoris
+inference: true
+widget:
+- text: 'unconditional (blank prompt)'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_0_0.png
+- text: 'hckl_style, A collection of radiolarians floating in water. Various species with different shapes and structures.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_1_0.png
+- text: 'hckl_style, A large jellyfish with trailing tentacles. Smaller jellyfish surround it in the ocean.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_2_0.png
+- text: 'hckl_style, A diverse coral reef ecosystem. Various types of coral, sea anemones, and small fish.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_3_0.png
+- text: 'hckl_style, An assortment of diatoms. Different species showcasing their unique geometric structures.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_4_0.png
+- text: 'hckl_style, hamster'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_5_0.png
+- text: 'hckl_style, a hipster making a chair'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_6_0.png
+- text: 'hckl_style, A detailed evolutionary tree diagram showing the relationships between various species.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_7_0.png
+- text: 'hckl_style, A modern microbiology laboratory with researchers using advanced microscopes and equipment.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_8_0.png
+- text: 'hckl_style, A bustling city street with skyscrapers, cars, and pedestrians.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_9_0.png
+- text: 'hckl_style, An orbiting space station with astronauts conducting experiments in zero gravity.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_10_0.png
+- text: 'hckl_style, A person scrolling through a social media feed on a smartphone, surrounded by floating app icons.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_11_0.png
+- text: 'hckl_style, A energetic rock band performing on stage with a large crowd in the foreground.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_12_0.png
+- text: 'hckl_style, A visual representation of artificial intelligence, with interconnected nodes and data streams.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_13_0.png
+- text: 'a hamster, hckl_style'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_14_0.png
+---
+
+# Flux-Ernst-Haeckel-LoKr
+
+This is a LyCORIS adapter derived from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev).
+
+
+The main validation prompt used during training was:
+
+
+
+```
+a hamster, hckl_style
+```
+
+## Validation settings
+- CFG: `3.0`
+- CFG Rescale: `0.0`
+- Steps: `25`
+- Sampler: `None`
+- Seed: `42`
+- Resolution: `1024x1024`
+
+Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
+
+You can find some example images in the following gallery:
+
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+
+## Training settings
+
+- Training epochs: 0
+- Training steps: 250
+- Learning rate: 0.0001
+- Effective batch size: 1
+  - Micro-batch size: 1
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 1
+- Prediction type: flow-matching
+- Rescaled betas zero SNR: False
+- Optimizer: adamw_bf16
+- Precision: Pure BF16
+- Quantised: Yes: int8-quanto
+- Xformers: Not used
+- LyCORIS Config:
+```json
+{
+    "algo": "lokr",
+    "multiplier": 1.0,
+    "linear_dim": 10000,
+    "linear_alpha": 1,
+    "factor": 16,
+    "apply_preset": {
+        "target_module": [
+            "Attention",
+            "FeedForward"
+        ],
+        "module_algo_map": {
+            "Attention": {
+                "factor": 16
+            },
+            "FeedForward": {
+                "factor": 8
+            }
+        }
+    }
+}
+```
+
+## Datasets
+
+### ernst-haeckel-flux-512
+- Repeats: 10
+- Total number of images: 81
+- Total number of aspect buckets: 1
+- Resolution: 0.262144 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### ernst-haeckel-flux-1024
+- Repeats: 10
+- Total number of images: 81
+- Total number of aspect buckets: 2
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### ernst-haeckel-flux-512-crop
+- Repeats: 10
+- Total number of images: 81
+- Total number of aspect buckets: 1
+- Resolution: 0.262144 megapixels
+- Cropped: True
+- Crop style: random
+- Crop aspect: square
+### ernst-haeckel-flux-1024-crop
+- Repeats: 10
+- Total number of images: 81
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: True
+- Crop style: random
+- Crop aspect: square
+
+
+## Inference
+
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+from lycoris import create_lycoris_from_weights
+
+model_id = 'black-forest-labs/FLUX.1-dev'
+adapter_id = 'pytorch_lora_weights.safetensors' # you will have to download this manually
+lora_scale = 1.0
+wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_id, pipeline.transformer)
+wrapper.merge_to()
+
+prompt = "a hamster, hckl_style"
+
+pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
+image = pipeline(
+    prompt=prompt,
+    num_inference_steps=25,
+    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
+    width=1024,
+    height=1024,
+    guidance_scale=3.0,
+).images[0]
+image.save("output.png", format="PNG")
+```
+