Model card auto-generated by SimpleTuner

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
+  - lora
+  - template:sd-lora
+inference: true
+
+---
+
+# simpletuner-lora-schedulefree
+
+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 photo-realistic image of a cat
+```
+
+## Validation settings
+- CFG: `3.0`
+- CFG Rescale: `0.0`
+- Steps: `20`
+- Sampler: `None`
+- Seed: `42`
+- Resolution: `1776x512`
+
+Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
+
+
+
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+
+## Training settings
+
+- Training epochs: 13
+- Training steps: 10001
+- Learning rate: 0.0001
+- Effective batch size: 6
+  - Micro-batch size: 2
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 3
+- Prediction type: flow-matching
+- Rescaled betas zero SNR: False
+- Optimizer: adamw_schedulefree+aggressiveweight_decay=1e-3
+- Precision: bf16
+- Quantised: Yes: fp8-quanto
+- Xformers: Not used
+- LyCORIS Config:
+```json
+{
+    "algo": "lokr",
+    "multiplier": 1.0,
+    "linear_dim": 10000,
+    "linear_alpha": 1,
+    "factor": 12,
+    "apply_preset": {
+        "target_module": [
+            "Attention",
+            "FeedForward"
+        ],
+        "module_algo_map": {
+            "Attention": {
+                "factor": 12
+            },
+            "FeedForward": {
+                "factor": 6
+            }
+        }
+    }
+}
+```
+
+## Datasets
+
+### garfield
+- Repeats: 0
+- Total number of images: ~2211
+- Total number of aspect buckets: 6
+- Resolution: 512 px
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+
+
+## 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 photo-realistic image of a cat"
+
+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=20,
+    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
+    width=1776,
+    height=512,
+    guidance_scale=3.0,
+).images[0]
+image.save("output.png", format="PNG")
+```
+