File size: 5,436 Bytes
6162f55
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
---
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
widget:
- text: 'unconditional (blank prompt)'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_0_0.png
- text: 'Dr. Seuss during a book signing event, seated at a table with an open book and pen in hand, his characteristic white beard, clear-rimmed glasses, and whimsical bow tie complementing his calm, attentive expression, all within the literary setting of a bookstore, reflecting his enduring connection with readers and the joy his work brought to many.'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_1_0.png
- text: 'Anime picture of famed author Dr. Seuss in a Studio Ghibli style'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_2_0.png
- text: 'Dr. Seuss in a leather jacket riding a Harley Davidson Motorcycle'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_3_0.png
- text: 'Famous author Dr. Seuss holding a chainsaw while riding around on a unicycle, vintage TV still from the Dick Van Dyke show'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_4_0.png
- text: 'A photograph of Dr. Seuss riding in a horse-drawn carriage'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_5_0.png
---

# flux-training-seuss-lora-bsz-4

This is a standard PEFT LoRA 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 photograph of Dr. Seuss riding in a horse-drawn carriage
```

## Validation settings
- CFG: `3.5`
- CFG Rescale: `0.0`
- Steps: `15`
- 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: 0
- Training steps: 100
- Learning rate: 0.0008
- Effective batch size: 4
  - Micro-batch size: 4
  - Gradient accumulation steps: 1
  - Number of GPUs: 1
- Prediction type: flow-matching
- Rescaled betas zero SNR: False
- Optimizer: adamw_bf16
- Precision: bf16
- Quantised: No
- Xformers: Not used
- LoRA Rank: 16
- LoRA Alpha: None
- LoRA Dropout: 0.1
- LoRA initialisation style: default
    

## Datasets

### default_dataset_arb
- Repeats: 100
- Total number of images: 4
- Total number of aspect buckets: 3
- Resolution: 1.5 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
### default_dataset
- Repeats: 100
- Total number of images: 3
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_512
- Repeats: 100
- Total number of images: 4
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_576
- Repeats: 100
- Total number of images: 4
- Total number of aspect buckets: 1
- Resolution: 0.331776 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_640
- Repeats: 100
- Total number of images: 4
- Total number of aspect buckets: 1
- Resolution: 0.4096 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_704
- Repeats: 100
- Total number of images: 4
- Total number of aspect buckets: 1
- Resolution: 0.495616 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_768
- Repeats: 100
- Total number of images: 3
- Total number of aspect buckets: 1
- Resolution: 0.589824 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_832
- Repeats: 100
- Total number of images: 3
- Total number of aspect buckets: 1
- Resolution: 0.692224 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_896
- Repeats: 100
- Total number of images: 3
- Total number of aspect buckets: 1
- Resolution: 0.802816 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### default_dataset_960
- Repeats: 100
- Total number of images: 3
- Total number of aspect buckets: 1
- Resolution: 0.9216 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square


## Inference


```python
import torch
from diffusers import DiffusionPipeline

model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'jimmycarter/flux-training-seuss-lora-bsz-4'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)

prompt = "A photograph of Dr. Seuss riding in a horse-drawn carriage"

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=15,
    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=3.5,
).images[0]
image.save("output.png", format="PNG")
```