odyss3y commited on
Commit
00daa94
·
verified ·
1 Parent(s): 14a7ebf

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +169 -3
README.md CHANGED
@@ -1,3 +1,169 @@
1
- ---
2
- license: creativeml-openrail-m
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: creativeml-openrail-m
3
+ tags:
4
+ - stable-diffusion-v1-5
5
+ - image-generation
6
+ - not-for-all-audiences
7
+ - uncanny-valley
8
+ - art
9
+ - fantasy
10
+ - fashion
11
+ - beauty
12
+ - female-focus
13
+ language:
14
+ - en
15
+ ---
16
+
17
+ # Model Card for Aberrated Perceptron
18
+
19
+ ## Model Details
20
+
21
+ ### Model Description
22
+
23
+ Aberrated Perceptron is a Stable Diffusion 1.5 model primarily tuned for women's fashion, beauty, and fantasy art. Developed by the user **odyss3y**, this model excels at generating hyper-realistic images, particularly within the uncanny valley of realism. The intention behind Aberrated Perceptron is not to achieve photo-quality images but to push the boundaries of realism within the context of AI-generated art. This model is designed to be more realistic than its counterpart, Recursed Canvas, with which it is frequently blended.
24
+
25
+ Blending Aberrated Perceptron with Recursed Canvas using tools like A1111’s refiner, hires, and in-painting techniques (including Adetailer) has yielded fascinating results. The blending process typically involves using Recursed Canvas as the base for the first 20-95% of the image generation, with Aberrated Perceptron adding its unique touch of realism.
26
+
27
+ The model serves as a benchmark in exploring the strengths, weaknesses, and limitations of realistic image generation within the Stable Diffusion 1.5 framework.
28
+
29
+ - **Developed by:** odyss3y
30
+ - **Funded by:** Personal
31
+ - **Shared by:** odyss3y
32
+ - **Model type:** Stable Diffusion 1.5, focused on fashion, beauty, and fantasy art
33
+ - **Language(s) (NLP):** N/A
34
+ - **License:** CreativeML OpenRAIL-M
35
+ - **Finetuned from model:** N/A (Based entirely on merges with other models)
36
+
37
+ ### Model Sources
38
+
39
+ - **Repository:** Refer to the changelog for specific version information.
40
+
41
+ ## Uses
42
+
43
+ ### Direct Use
44
+
45
+ Aberrated Perceptron is intended for generating art with a female focus, emphasizing beauty, fashion, and fantasy storytelling. It is ideal for artists and creatives seeking to explore hyper-realistic yet artistically enhanced imagery within these domains.
46
+
47
+ ### Out-of-Scope Use
48
+
49
+ The model should not be used in ways that violate ethical guidelines, including but not limited to the creation of misleading or harmful content, especially involving real people or depictions of children. Users must comply with all relevant laws and ethical standards when using this model.
50
+
51
+ ## Bias, Risks, and Limitations
52
+
53
+ The model has been overfitted with imagery of beautiful women, likely resulting in biased outputs that skew towards this direction. Users should be aware of this bias when generating images and consider the ethical implications of such biases.
54
+
55
+ ### Recommendations
56
+
57
+ Users should carefully consider the potential biases and ethical concerns when using Aberrated Perceptron. It is recommended to avoid generating content that could be harmful or offensive, particularly involving sensitive subjects like real individuals or minors.
58
+
59
+ ## How to Get Started with the Model
60
+
61
+ Use the following code to get started with Aberrated Perceptron:
62
+
63
+ ```python
64
+ # Example code to load the model
65
+ from diffusers import StableDiffusionPipeline
66
+
67
+ model_id = "path_to_aberrated_perceptron_model"
68
+ pipe = StableDiffusionPipeline.from_pretrained(model_id)
69
+ pipe.to("cuda")
70
+
71
+ prompt = "a hyper-realistic portrait of a woman in a fantasy setting"
72
+ image = pipe(prompt).images[0]
73
+ image.show()
74
+ ```
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ This model is based entirely on merges with other models, leveraging their strengths to achieve the desired effects in image generation. There was no specific dataset used for fine-tuning or additional training.
81
+
82
+ ### Training Procedure
83
+
84
+ No direct training was performed on Aberrated Perceptron. The model's capabilities were shaped through the careful merging of existing models, using techniques such as Merge Block Weighting (MBW).
85
+
86
+ #### Preprocessing
87
+
88
+ N/A
89
+
90
+ #### Training Hyperparameters
91
+
92
+ - **Training regime:** N/A (No direct training performed)
93
+
94
+ #### Speeds, Sizes, Times
95
+
96
+ - **Merging Time:** Momentary, depending on the merge method used.
97
+ - **Evaluation Time:** Approximately 18 hours of GPU time on an NVIDIA GeForce RTX 3060 Ti.
98
+
99
+ ## Evaluation
100
+
101
+ ### Testing Data, Factors & Metrics
102
+
103
+ #### Testing Data
104
+
105
+ Standardized prompts were used to evaluate the model's performance, particularly focusing on the effects of various merge processes.
106
+
107
+ #### Factors
108
+
109
+ The evaluation considered the realism and artistic quality of generated images, disaggregated by variations in merge processes and prompt adjustments.
110
+
111
+ #### Metrics
112
+
113
+ The primary evaluation metrics were subjective assessments of image realism, alignment with artistic goals, and the ability to generate desired effects within the model's intended scope.
114
+
115
+ ### Results
116
+
117
+ The model successfully achieved its intended purpose of generating hyper-realistic images within the uncanny valley of realism, with an emphasis on fashion, beauty, and fantasy art. The merging process with Recursed Canvas provided a versatile toolset for balancing realism and artistic expression.
118
+
119
+ ## Environmental Impact
120
+
121
+ The carbon emissions for training and evaluating Aberrated Perceptron can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute).
122
+
123
+ - **Hardware Type:** NVIDIA GeForce RTX 3060 Ti
124
+ - **Hours used:** Approximately 18 hours
125
+ - **Cloud Provider:** N/A
126
+ - **Compute Region:** USA
127
+ - **Carbon Emitted:** [Calculation Needed]
128
+
129
+ ## Technical Specifications
130
+
131
+ ### Model Architecture and Objective
132
+
133
+ Aberrated Perceptron utilizes the Stable Diffusion 1.5 architecture with a focus on realistic yet artistically enhanced image generation in the domains of fashion, beauty, and fantasy.
134
+
135
+ ### Compute Infrastructure
136
+
137
+ #### Hardware
138
+
139
+ - NVIDIA GeForce RTX 3060 Ti
140
+
141
+ #### Software
142
+
143
+ - A1111 with refiner, hires, and in-painting techniques (Adetailer)
144
+
145
+ ## Citation
146
+
147
+ **BibTeX:**
148
+
149
+ [More Information Needed]
150
+
151
+ **APA:**
152
+
153
+ [More Information Needed]
154
+
155
+ ## Glossary [optional]
156
+
157
+ N/A
158
+
159
+ ## More Information [optional]
160
+
161
+ [More Information Needed]
162
+
163
+ ## Model Card Authors
164
+
165
+ Model card authored by odyss3y.
166
+
167
+ ## Model Card Contact
168
+
169
+ For inquiries, please contact [contact information if desired].