File size: 1,923 Bytes
524b424
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
687a48b
524b424
 
 
 
 
 
 
687a48b
524b424
 
 
 
 
 
 
ef0f212
524b424
 
 
 
 
 
 
 
 
 
 
 
 
 
ef0f212
 
 
 
 
 
 
 
 
 
 
524b424
 
 
 
ef0f212
524b424
 
 
ef0f212
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
---
base_model: OnomaAIResearch/Illustrious-xl-early-release-v0
library_name: diffusers
license: openrail++
tags:
- text-to-image
- text-to-image
- diffusers-training
- diffusers
- lora
- template:sd-lora
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
widget: []
---

<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->


# SDXL LoRA - NLPBada/base_LoRA_512_512_bs6_step200

<Gallery />

## Model description

These are NLPBada/base_LoRA_512_512_bs6_step200 LoRA adaption weights for OnomaAIResearch/Illustrious-xl-early-release-v0.

The weights were trained  using 

LoRA for the text encoder was enabled: False.

Special VAE used for training: None.

## Trigger words

You should use ""In the style of irasutoya," to trigger the image generation.

## Download model

Weights for this model are available in Safetensors format.

[Download](NLPBada/base_LoRA_512_512_bs6_step200/tree/main) them in the Files & versions tab.



## Intended uses & limitations

#### How to use

```python
#Adjusted guidance_scale + Negative Prompt
width = 1024 
height = 1024 
num_inference_steps = 60 
guidance_scale = 5.5 
# prompt = "In the style of irasutoya, 1girl, lightblue collared shirt, smiling with mouth closed, wearing glasses, eyes not visible, furrowed eyebrows, black bobbed parted hair" # @param
prompt = "In the style of irasutoya a boy wearing a darkcyan shirt, smiling with mouth closed, furrowing eyebrows, black pouty hair, upper body" # @param
negative_prompt = "duplicates, worst quality, bad quality, low quality, scan artifacts, jaggy lines, unclear" #@param

image = pipe(prompt, num_inference_steps=num_inference_steps, width=width, height=height, guidance_scale=guidance_scale).images[0]
image
```

#### Limitations and bias

pending

## Training details

pending