ネガティブエンベッドの導入と使用方法解説！もう長いプロンプトはおしまい！【Stable Diffusion】
TLDRThis video script introduces the concept of Negative Embeds in AI-generated art, highlighting their utility in refining image quality. The host explains the frustration with negative prompts and presents EasyNegative as a solution, demonstrating its application and effect on image generation. Various embeds like 'Bad Prompt', 'Bad Artist', and 'Deep Negative' are discussed, each with specific recommendations for use. The video encourages viewers to explore and find their preferred embed for enhancing AI-generated images.
Takeaways
- 📝 Negative prompts are a method used to guide AI away from undesired outputs, but they can be bothersome to input repeatedly.
- 🌐 There's no definitive solution in spell writing, hence the global adoption of negative embeds to simplify the process.
- 📚 Embeddings are essentially instructions filled in to guide AI, and in the context of Stable Diffusion, they refer to learning files.
- 🤖 AI can be trained over time to follow instructions in a 'memo', which is an embed, without needing long explanations each time.
- 🚀 EasyNegative is a representative negative embed that simplifies the input process for generating images with Stable Diffusion.
- 🔍 To use EasyNegative, access Hugging Face, search for it, and download the SafeTensors file to install in the web UI's embeddings folder.
- 🎨 The use of EasyNegative significantly improves image quality, providing crisper and clearer outputs compared to using no negative prompts at all.
- 📈 EasyNegative can be adjusted for effect, such as using 1.5 times the strength for even clearer images.
- 💾 Saved templates with embedded prompts can be quickly accessed and used for generating images, streamlining the process.
- 🧩 Other negative embeds exist, such as 'Bad Prompt 1 and 2', 'Bad Artist', and 'Deep Negative', each with specific recommendations for use.
- 🎓 It's recommended to start with EasyNegative and consider adding Deep Negative for additional quality improvement, without overemphasizing its use.
Q & A
What is the main topic of the video?
-The main topic of the video is the introduction and use of negative embeds in AI, specifically focusing on EasyNegative and other similar tools to improve image generation quality.
What is the purpose of using negative prompts in AI?
-Negative prompts are used to instruct AI to avoid certain undesirable outcomes or to refine the generation process, ensuring the AI follows the user's intentions more closely.
What does the term 'embeddings' refer to in the context of AI and Stable Diffusion?
-In the context of AI and Stable Diffusion, embeddings refer to learned files or data structures that capture the patterns and meanings of language, which are used to guide the AI's generation process.
How does the speaker describe the process of using negative embeds?
-The speaker describes the process as initially bothersome, requiring the user to instruct the AI on what not to do over a long period. However, with the use of a memo (embed), the AI can follow these instructions without the need for repeated explanations.
What is EasyNegative and how is it used?
-EasyNegative is a representative negative embed that simplifies the process of inputting negative prompts. It can be used by accessing Hugging Face, searching for it, downloading the SafeTensors file, and placing it in the embeddings folder of the web UI. Users then simply type 'EasyNegative' in the negative prompt line to utilize it.
How does the video demonstrate the effect of using EasyNegative?
-The video demonstrates the effect of using EasyNegative by generating an image of a girl with and without the use of EasyNegative. The comparison shows that images generated with EasyNegative are clearer and of higher quality.
What other negative embeds are mentioned in the video?
-Other negative embeds mentioned in the video include 'Bad Prompt 1 and 2' by NerfGun3, 'Bad Artist' by NixerHatter59, and 'Deep Negative' by FapMagi.
What is the recommended usage for the 'Deep Negative' embed?
-The 'Deep Negative' embed is recommended to be used in combination with quality prompts and other embeds, as it is dedicated to preventing the collapse of the model and structure, and may not significantly improve image quality on its own.
How can users save and recall their preferred prompts in the web UI?
-Users can save their preferred prompts by clicking on the floppy button under the Generate button, naming the prompt, and clicking OK. To recall a saved prompt, users can click on the second trash can button from the left, select the saved template from the pull-down menu under the Generate button, and click on the brown binder button to paste the template in the prompt column.
What is the speaker's advice for users interested in trying out negative embeds?
-The speaker advises users to start with EasyNegative and, if they feel comfortable, experiment with adding other embeds like Deep Negative, but to the extent that it does not overly emphasize the negative aspects.
How does the video conclude?
-The video concludes with an encouragement for viewers to explore and find their favorite embeds, and the speaker wishes everyone well with a reminder to eat properly and thanks the viewers for watching.
Outlines
🎨 Introduction to Negative Embeds in AI Art Generation
This paragraph introduces the concept of negative prompts and embeds in AI art generation. It discusses the challenges of using negative prompts and how they can be cumbersome. The speaker explains that negative embeds, like the one called EasyNegative, can be used to instruct AI to avoid undesired outcomes. The process of using EasyNegative, including accessing Hugging Face, downloading the embed, and applying it in the web UI, is outlined. The effects of using EasyNegative are demonstrated by comparing images generated with and without it, highlighting the improved clarity and quality. The paragraph also mentions other negative embeds like 'Bad Prompt 1 and 2' and 'Bad Artist,' suggesting that users explore different options to find their preferred embed.
📚 Exploring Additional Negative Embeds and Their Applications
This paragraph continues the discussion on negative embeds, focusing on 'Deep Negative' created by FapMagi. It explains that 'Deep Negative' is designed to prevent the collapse of model and structure in generated images, but may not significantly enhance image quality on its own. The speaker suggests using 'Deep Negative' in conjunction with quality prompts and other embeds for better results. The paragraph concludes with a recommendation to try out EasyNegative and Deep Negative to find the most suitable embed for individual preferences. The speaker signs off by encouraging proper eating and thanking the viewers for watching.
Mindmap
Keywords
💡Negative Embeds
💡Stable Diffusion
💡Embeddings
💡EasyNegative
💡Prompts
💡Web UI
💡Quality
💡Upscale
💡Templates
💡Negative Prompts
💡Deep Negative
Highlights
The discussion revolves around the concept and use of negative prompts in AI-generated images.
Negative prompts are acknowledged as a global hassle in the AI community.
Embeddings, particularly negative embeddings, are introduced as a solution to the inconvenience of negative prompts.
Negative embeddings are files that instruct AI to avoid certain undesired outcomes.
The process of using negative embeddings involves placing them in the AI's installation folder and activating them through the user interface.
EasyNegative is highlighted as a representative negative embedding.
Instructions for accessing EasyNegative on Hugging Face are provided.
EasyNegative is used to improve the quality of AI-generated images by avoiding common issues.
The practical application of EasyNegative is demonstrated by comparing images generated with and without it.
The impact of EasyNegative on image clarity and quality is emphasized.
EasyNegative can be combined with other adjustments for further refinement.
The process of saving and recalling templates for efficient use is explained.
Additional negative embeddings such as 'Bad Prompt 1 and 2', 'Bad Artist', and 'Deep Negative' are introduced.
Recommendations for using these negative embeddings are provided, including adjustments for optimal results.
The importance of finding the right negative embedding for individual needs is highlighted.
The session concludes with an encouragement to explore and find one's preferred negative embedding.
The presenter wishes the audience well and expresses gratitude for their attention.