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README.md

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-
-
-# flux-lora-littletinies
-
-This is a LoRA derived from [FLUX.1-dev/](https://huggingface.co//workspace/SimpleTuner/FLUX.1-dev/).
-
-
-
-The main validation prompt used during training was:
-
-```
-ethnographic photography of teddy bear at a picnic
-```
-
-## Validation settings
-- CFG: `7.5`
-- CFG Rescale: `0.7`
-- Steps: `50`
-- Sampler: `None`
-- Seed: `42`
-- Resolution: `1024`
-
-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: 23
-- Training steps: 1800
-- Learning rate: 0.0001
-- Effective batch size: 16
-  - Micro-batch size: 8
-  - Gradient accumulation steps: 2
-  - Number of GPUs: 1
-- Prediction type: epsilon
-- Rescaled betas zero SNR: False
-- Optimizer: AdamW, stochastic bf16
-- Precision: Pure BF16
-- Xformers: Enabled
-- LoRA Rank: 64
-- LoRA Alpha: 16
-- LoRA Dropout: 0.1
-- LoRA initialisation style: default
-
-
-## Datasets
-
-### little-tinies
-- Repeats: 18
-- Total number of images: 64
-- Total number of aspect buckets: 1
-- Resolution: 1.0 megapixels
-- Cropped: False
-- Crop style: None
-- Crop aspect: None
-
-
-## Inference
-
-
-```python
-import torch
-from diffusers import DiffusionPipeline
-
-model_id = '/pzc163/flux-lora-littletinies'
-adapter_id = 'flux-lora-littletinies'
-pipeline = DiffusionPipeline.from_pretrained(model_id)\pipeline.load_adapter(adapter_id)
-
-prompt = "ethnographic photography of teddy bear at a picnic"
-negative_prompt = "blurry, cropped, ugly"
-
-pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
-image = pipeline(
-    prompt=prompt,
-    negative_prompt='blurry, cropped, ugly',
-    num_inference_steps=50,
-    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
-    width=1152,
-    height=768,
-    guidance_scale=7.5,
-    guidance_rescale=0.7,
-).images[0]
-image.save("output.png", format="PNG")
-```
-
-inference: true
-widget:
-- text: 'unconditional (blank prompt)'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./image0.png
-- text: 'ethnographic photography of teddy bear at a picnic'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-  output:
-    url: ./image1.png
-- text: 'a robot walking on the street,surrounded by a group of girls'
-  parameters:
-    negative_prompt: 'blurry, cropped, ugly'
-