zwloong commited on
Commit
e811654
1 Parent(s): 3204b46

Model card auto-generated by SimpleTuner

Browse files
Files changed (1) hide show
  1. README.md +117 -0
README.md ADDED
@@ -0,0 +1,117 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: other
3
+ base_model: "stabilityai/stable-diffusion-3-medium-diffusers"
4
+ tags:
5
+ - sd3
6
+ - sd3-diffusers
7
+ - text-to-image
8
+ - diffusers
9
+ - simpletuner
10
+ - lora
11
+ - template:sd-lora
12
+ inference: true
13
+ widget:
14
+ - text: 'unconditional (blank prompt)'
15
+ parameters:
16
+ negative_prompt: 'blurry, cropped, ugly'
17
+ output:
18
+ url: ./assets/image_0_0.png
19
+ - text: 'ethnographic photography of teddy bear at a picnic'
20
+ parameters:
21
+ negative_prompt: 'blurry, cropped, ugly'
22
+ output:
23
+ url: ./assets/image_1_0.png
24
+ ---
25
+
26
+ # sd3-lora-training-rank16
27
+
28
+ This is a standard PEFT LoRA derived from [stabilityai/stable-diffusion-3-medium-diffusers](https://huggingface.co/stabilityai/stable-diffusion-3-medium-diffusers).
29
+
30
+
31
+ The main validation prompt used during training was:
32
+
33
+
34
+
35
+ ```
36
+ ethnographic photography of teddy bear at a picnic
37
+ ```
38
+
39
+ ## Validation settings
40
+ - CFG: `4.0`
41
+ - CFG Rescale: `0.0`
42
+ - Steps: `30`
43
+ - Sampler: `None`
44
+ - Seed: `42`
45
+ - Resolution: `1024x1024`
46
+
47
+ Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
48
+
49
+ You can find some example images in the following gallery:
50
+
51
+
52
+ <Gallery />
53
+
54
+ The text encoder **was not** trained.
55
+ You may reuse the base model text encoder for inference.
56
+
57
+
58
+ ## Training settings
59
+
60
+ - Training epochs: 2
61
+ - Training steps: 74
62
+ - Learning rate: 8e-07
63
+ - Effective batch size: 2
64
+ - Micro-batch size: 1
65
+ - Gradient accumulation steps: 2
66
+ - Number of GPUs: 1
67
+ - Prediction type: flow-matching
68
+ - Rescaled betas zero SNR: False
69
+ - Optimizer: adamw_bf16
70
+ - Precision: bf16
71
+ - Quantised: No
72
+ - Xformers: Not used
73
+ - LoRA Rank: 16
74
+ - LoRA Alpha: None
75
+ - LoRA Dropout: 0.1
76
+ - LoRA initialisation style: default
77
+
78
+
79
+ ## Datasets
80
+
81
+ ### Pal
82
+ - Repeats: 0
83
+ - Total number of images: 73
84
+ - Total number of aspect buckets: 1
85
+ - Resolution: 1.048576 megapixels
86
+ - Cropped: True
87
+ - Crop style: center
88
+ - Crop aspect: square
89
+
90
+
91
+ ## Inference
92
+
93
+
94
+ ```python
95
+ import torch
96
+ from diffusers import DiffusionPipeline
97
+
98
+ model_id = 'stabilityai/stable-diffusion-3-medium-diffusers'
99
+ adapter_id = 'zwloong/sd3-lora-training-rank16'
100
+ pipeline = DiffusionPipeline.from_pretrained(model_id)
101
+ pipeline.load_lora_weights(adapter_id)
102
+
103
+ prompt = "ethnographic photography of teddy bear at a picnic"
104
+ negative_prompt = 'blurry, cropped, ugly'
105
+ pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
106
+ image = pipeline(
107
+ prompt=prompt,
108
+ negative_prompt=negative_prompt,
109
+ num_inference_steps=30,
110
+ generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
111
+ width=1024,
112
+ height=1024,
113
+ guidance_scale=4.0,
114
+ ).images[0]
115
+ image.save("output.png", format="PNG")
116
+ ```
117
+