Model Card for Model ID
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Model Details
Model Description
- Developed by (English name): Tasty-Rice
- Developed by (Chinese name): 米饭不好吃
- Model type: [Diffusion based text to image generative model]
- Language(s) (NLP): [English]
- License: CC-BY-NC-SA-4.0
Model Sources [optional]
Sample Picture
Magic_on_paper-v1
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Illusionary dimension-v1
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Multi Aspect Resolution
并非所有的分辨率都支持的非常好，但遵循这样的分辨率使用你将得到更好的体验。 Not all resolutions support very well, but following these resolutions will give you a better experience. This model supports generating images at the following dimensions:
| Dimensions | Aspect Ratio | Dimensions | Aspect Ratio |
|---|---|---|---|
1024 x 1024 |
1:1 Square | ||
704×1408 |
1:2 | 1408×704 |
2:1 |
1472×704 |
23:11 | 704×1344 |
11:21 |
960×1024 |
15:16 | 1024×960 |
16:15 |
960×1088 |
15:17 | 1088×960 |
17:15 |
896×1088 |
14:17 | 1088×896 |
17:14 |
896×1152 |
7:9 | 1152×896 |
9:7 |
832×1152 |
13:18 | 1152×832 |
18:13 |
832×1216 |
13:19 | 1216×832 |
19:13 |
768×1280 |
3:5 | 1280×768 |
5:3 |
768×1344 |
4:7Vertical | 1344×768 |
7:4Horizontal |
1536×640 |
12:5 | 1600×640 |
5:2 |
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
好吃米-写实-SD-2.1-v1
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Uses
Notice/The content of the additional terms
| Number | Terms and Conditions |
|---|---|
| 1 | Do not host this model or its derivatives on websites/applications that generate income or donations. For commercial use, please contact the owner through the platform. |
| 2 | Do not directly sell generated images unless they have undergone sufficient manual modification and are deemed personal works. Violators will be subject to legal consequences. |
| 3 | Do not intentionally create or share illegal or harmful content. Please abide by public order and morality, and use it for positive purposes. |
| 4 | By using this model, you agree to all terms and conditions. |
| 5 | The model is limited to personal use and cannot be used for commercial purposes. |
| 6 | Do not use the model for illegal or harmful purposes, such as infringing rights, spreading false information, etc. |
| 7 | Users shall abide by all applicable laws and regulations, including safety, data protection, etc. |
| 8 | Respect the rights of others and do not infringe the rights of third parties. |
| 9 | Disputes or lawsuits shall be borne by the user's own legal responsibility. |
| 10 | Take necessary technical and management measures to ensure data security and confidentiality. |
| 11 | Comply with intellectual property laws and do not infringe the intellectual property rights of third parties. |
| 12 | Do not exploit or harm minors, and do not involve content, activities, or services related to minors. |
| 13 | Do not generate or disseminate verifiable false information or content that harms others. |
| 14 | Do not defame, discredit, or harass others in any other way. |
| 15 | Do not make fully automated decisions that adversely affect the legitimate rights of individuals or create legal obligations. |
| 16 | Do not discriminate or harm individuals or groups, including based on social behavior or known characteristics. |
| 17 | Do not exploit the vulnerabilities of specific groups, distort related behaviors, and cause or potentially cause physical or psychological harm. |
| 18 | Do not discriminate or harm based on protected characteristics or categories. |
| 19 | Do not use for medical consultation or interpretation of medical results. |
| 20 | Do not generate or disseminate information for judicial, law enforcement, immigration, or asylum proceedings, such as predicting criminal behavior. |
Direct Use
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Downstream Use [optional]
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
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Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Summary
Model Examination [optional]
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation [optional]
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Glossary [optional]
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