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Hello everyone, 🥰 Christmas is coming up, so I would like to introduce some words that you should include in your prompts to create better works using the Christmas model for image generation.First of allIn AI image generation, the choice of words in the prompt you use greatly affects the quality of the image. In this article, we will introduce some tips that are easy to understand even for beginners and will improve the quality of your images not only for Christmas but also for everyday prompts.1. Basic strategyTo create an effective prompt, keep the following points in mind. By keeping these in mind, it will be easier for AI to generate images that meet your intentions.Style: Specifies the atmosphere and drawing method of the image.Examples: "anime style", "cyberpunk", "watercolor painting", "Ink painting style", "Reality Photo", etc.Type: Indicates the composition of the image.Examples: "portrait", "landscape", "full-body character", "Cowboy Shot", etc.Background: Clarify the situation and background of the image.Examples: "sunset", "dense forest", "futuristic cityscape", etc.Mood: Set the overall atmosphere of the image.Examples: "dramatic", "peaceful", "vibrant", etc.2. Elements to emphasize and examples of their useTo have the AI ​​reflect specific elements, use the following phrases.Lighting effects:"golden hour lighting"Example: "a serene mountain landscape, golden hour lighting, highly detailed""neon glow"Example: "a cyberpunk city at night, neon glow, atmospheric"Camera perspective:"close-up of a face"Example: "a close-up of a young woman's face, freckles, cinematic lighting""wide-angle view"Example: "a wide-angle view of a bustling market, colorful stalls, lively atmosphere"Background details:"galaxy in the background"Example: "a futuristic spacecraft, galaxy in the background, vibrant colors""snow-covered mountains"Example: "a hiker on a snowy trail, snow-covered mountains, dramatic lighting"Texture:"highly detailed"Example: "a dragon with highly detailed scales, glowing eyes, fantasy setting""soft and fluffy texture"Example: "a kitten sleeping on a blanket, soft and fluffy texture, warm lighting"3. Techniques for adding originalityAdding the following phrases will give you a more unique result:Abstract/Fantastic elements:"ethereal"Example: "an ethereal fairy in a glowing forest, delicate wings, magical atmosphere""surreal"Example: "a surreal desert with floating islands, warm tones, imaginative"Luminescence and special effects:"bioluminescent"Example: "an underwater world with bioluminescent plants, vibrant colors, mysterious""iridescent"Example: "a bird with iridescent feathers, perched on a branch, sunlight reflection"Environment and atmosphere:"dystopian"Example: "a dystopian cityscape, dark and foggy, neon lights""whimsical"Example: "a whimsical tea party in a garden, pastel colors, surreal elements"4. Tips to avoid problemsSome words and settings may cause the AI ​​to produce unstable results. Please refer to the following and adjust the prompts.Words to avoid:"blurry""chaotic"Suggested alternatives:"soft focus" → Example: "a soft focus portrait of a smiling elderly woman, warm lighting""dynamic composition" → Example: "a dynamic composition of a sports car racing on a track, motion blur"5. Further examples of AI image generationCharacter design: Example: "a steampunk warrior with intricate armor, full-body, dramatic lighting"Product promotion: Example: "a sleek smartphone on a reflective surface, minimalistic design, vibrant colors"Recreating an art style: Example: "a serene landscape in the style of Van Gogh, swirling brushstrokes, vivid colors"6. Example Christmas-themed promptFinally, I'll show you an example prompt to create a Christmas-themed image of a girl using my Christmas model "🎄Cute Christmas collection・FLUX 🎄" using the words introduced above. Use these as a starting point to create your own original prompts.*Fantastic Christmas"A young girl in a red and white Christmas dress, surrounded by glowing fairy lights, snowy background, whimsical atmosphere, vibrant colors, golden hour lighting"*Traditional Christmas scene"A cheerful girl decorating a Christmas tree, cozy living room, soft and warm lighting, fireplace in the background, soft and fluffy texture"*Futuristic Christmas"A futuristic Christmas celebration, a girl in a glowing cyberpunk Santa outfit, neon lights, snowy futuristic cityscape, vibrant and dynamic composition"*Winter fairy girl"A snow fairy girl with delicate wings, sparkling snowflakes, ethereal and magical atmosphere, soft focus, iridescent glow"*Christmas market at night"A young girl walking through a bustling Christmas market, surrounded by festive stalls and twinkling lights, wide-angle view, atmospheric"Tweak these prompts and enjoy your own Christmas images!Enjoy an amazing AI-generated experience! 🎄✨

　IntroductionHello everyone. In this article, we will explain the basic mechanism for creating AI tools with "Tensor Art". We will introduce the particularly important meanings of "workflow" and "node", how to set them up, and procedures.　What is an AI tool?AI Tools is a node-based tool for visually designing AI image generation. It consists of a processing flow (workflow) that combines nodes (like pieces of a puzzle) to generate an image.Main features of workflowIntuitive operability: simply place and connect nodes with drag and drop.Flexible configuration: Fully customize models (checkpoints), LoRA, prompts, and more.Real-time generation: You can start image generation immediately after setting.It is important to understand first!　What is a node?A node is a "small unit responsible for one process" in image generation. For example, there are nodes such as "Load Checkpoint" that loads an AI model and "CLIP Text Encode" that analyzes prompts.　Basic configuration of a node:Input: Materials that start processing (e.g. prompt or model).Output: Passes the results of processing to the next node.In an analogy, nodes are like the "parts" of a pipeline. Connecting these together creates the overall flow.　What is a workflow?A workflow is a series of image generation flows designed by connecting multiple nodes.For example, create the following flow:Load an AI model (Load Checkpoint)Analyze the prompt (Prompt Encode)Generate an image (Sampler)Save the image (Save Node)Visually constructing these flows enables image generation in Tensor Art.Image Generation Workflow in Tensor Art: Basic Configuration and StepsBelow, we will explain the basic workflow and the role of each node in detail.　Overview of the Basic Workflow　The basic configuration for image generation in Tensor Art is as follows:Load Checkpoint (AI model): Select the base generative model.→ Node name: Load CheckpointEncode prompt (generation instruction): Specify the direction of image generation.→ Node name: CLIP Text EncodeApply LoRA model (optional): Add style and features.→ Node name: Load LoRAImage generation process: Generate image based on prompt and model.→ Node name: KSamplerVAE decode: Adjust generated image to make it human-readable.→ Node name: VAE DecodeSave image: Save generated image to file.→ Node name: Save ImageDetailed explanation and setting method for each node　　　　　　　　　🌸⬇️Let's use a workflow using FLUX as an example. ⬇️🌸1. Load CheckpointRole: Loads the model that is the basis of AI image generation.Settings: ckpt_name: Specify the model name you want to use.Example: FLUX-1-dev-fp8 (recommended checkpoint for TensorArt).2. Load LoRA (Add style)Role: Apply LoRA model that adds specific features and style.Settings: lora_name: Enter the name of the LoRA model you want to use.strength_model and strength_clip: Model influence (1.0 recommended).3. CLIP Text EncodeRole: Converts the content of the image to be generated (prompt) into a format that AI can understand.Settings:Example prompt: "futuristic cityscape, neon lights, digital painting".4. KSampler (Central process of image generation)Role: Generates the actual image based on the prompt and model.Settings:steps: Accuracy of generation (approximately 20-30).cfg: Applicability of the prompt (usually 1.0).sampler_name: Sampling method (e.g. Euler).5. VAE DecodeRole: Converts the generated latent image into the final image data.Note: Select a VAE that corresponds to the checkpoint.6. Save ImageRole: Saves the generated image as a file.Settings:filename_prefix: Specifies the beginning of the image name (e.g. "TensorArt_").Example of actual workflow: Node connectionBelow is an example of an actual node connection. Image generation is possible by reproducing this flow in the Tensor Art node editor.Load Checkpoint → Load the AI ​​model.Add Load LoRA if necessary and apply styles.Enter prompts into CLIP Text Encode and set the generation content.Use FluxGuidance (adjust guidance scale) to fine-tune the influence of the prompt.Generate an image with KSampler.Adjust the image through VAE Decode.Finally, save the image with Save Image.　Frequently Asked QuestionsQ1. What is the difference between Checkpoint and LoRA?Checkpoint: A model that is the basis of AI image generation. It determines the overall style.LoRA: A module for adding specific additional styles and fine features.Q2. Is VAE required?Basically used in conjunction with Checkpoint. Without VAE, the color and resolution of the image may not be displayed properly.　SummaryOnce you understand how nodes and workflows work, you can create your own images just the way you want them. Use this guide to get started with a simple setup! 😆👍　　　　　　　　　　　⬆️This is an image generated using the workflow introduced this time 😊　Next stepsTry your own prompts and settings.Combine multiple LoRAs to pursue originality.Experiment with high resolution and special styles.By publishing the completed workflow, you can have many people use it as your AI tool 👍Enjoy your creative adventure with Tensor Art!　Side note: Tips for beginnersUnderstand the basics of nodes: First, understand what each node does.Start with a simple workflow: Try a workflow with a minimum number of nodes to help you understand how it works.Repeat the experiment: Adjust the parameters of each node and see how the generated image changes.

When it comes to AI image generation, there are several parameters you can tweak to create the exact image you have in mind. One of the most important factors is the Guidance Scale.In this post, we’ll explain what the guidance scale is, how it works, and the best way to set it for your projects!　　　　　　　　⚠️This is just my personal opinion and does not guarantee results. ⚠What is the Guidance Scale?The Guidance Scale is a setting that controls how strictly the AI follows the prompt (the input instructions). In other words, it determines how closely the AI sticks to the given instructions when generating an image.For example, if the guidance scale is set low, the AI will generate more creative, free-form images. On the other hand, if the guidance scale is set high, the AI will produce results that are closer to what’s specified in the prompt.How Does the Guidance Scale Affect the Image?The value of the guidance scale has a significant impact on the generated image. Let’s explore how different settings influence the outcome.This time, I tested it by changing only the guidance scale value with the same prompt and the same settings.prompt: Anime girl, looking at the viewer, retro, sitting on a red scooter, soft smile, super cute face, soft color, blush, dreamy,　(I borrowed the prompt from @JSP-san)　　　　　　　　　　　　　　　　　　So, let's compare~😉1. Low Guidance Scale (3–6)With a lower guidance scale, the AI has more freedom, so the images generated are less tightly bound to the prompt. This can lead to more abstract or unexpected elements in the image.Best used for: Abstract art or creative pieces where you want to embrace the AI’s imaginative interpretation.2. Moderate Guidance Scale (7–10)Setting the guidance scale to 7–10 offers a good balance, where the AI follows the prompt relatively closely but still incorporates some of its own creative adjustments. This is a versatile setting that works well for many scenarios, producing natural-looking images.Best used for: Realistic landscapes, portraits, or fantasy illustrations where you want a faithful but flexible interpretation.3. High Guidance Scale (12–15)With a high guidance scale, the AI will adhere very strictly to the prompt, ensuring detailed and precise results. However, if the value is set too high, the image might appear rigid or unnatural.Best used for: When you need exact details to be reflected in the image, such as specific character designs or highly structured compositions.（ In testing, settings between 12 and 15 resulted in images that were stiff, crumbly, and far from the prompt. ）How to Set the Guidance Scale for Optimal ResultsThe best guidance scale setting depends on the type of image you’re trying to generate, but starting with a scale between 7 and 10 is a good approach. From there, you can tweak the value based on the results you get, fine-tuning it to suit your needs.For creative and abstract images: Set the scale between 3 and 6.For natural and balanced results: Set it between 7 and 10.For precise and detailed results: Set it between 12 and 15？.Rather than aiming for perfection on the first try, experiment with different settings and enjoy the process of adjusting the scale to achieve your desired outcome.ConclusionThe guidance scale is a crucial parameter that dictates how strictly the AI follows the input prompt. By adjusting the value, you can either embrace the AI’s creative freedom or ensure the image adheres closely to your specifications. Mastering the guidance scale will help you create images that match your vision, whether you're looking for imaginative interpretations or exact representations.I hope this guide helps you make the most of the guidance scale in your AI image generation adventures!🥰💞

Hello everyone. Today, I would like to introduce a feature of tensor.art that is often overlooked.[Enhanced Prompt] Have you heard of it?It's a feature that is a little inconspicuous on the image generation screen that you usually use, but it's very useful.1. What is this feature?The Prompt reinforcement automatically generates multiple prompts that are enhanced and reconstructed by AI using the words of the prompt you entered. This makes the original prompt richer and more diverse, and increases the variety of images generated.2. How to use:It's very easy!Enter the prompt: First, enter the prompt for the image you want to generate as you normally would.Click the prompt extension button: Click the "Enhance Prompt " button at the bottom right of the prompt input field.It's a feature that is a little inconspicuous on the image generation screen that you usually use, but it's very useful.3. Check the suggested prompts:The AI ​​automatically analyzes the prompt you entered and suggests multiple enhanced prompts.Several restructured and enhanced prompts appear.All you have to do is choose the prompt of your choice.Choose the prompt of your choice and click the Select button.It will be automatically filled in the prompt field.Then, generate as usual! !4. UtilizationBroaden your ideas: Using the prompt extension allows you to discover new expressions and ideas that you never thought of.Improve the quality of your projects: Using more sophisticated prompts can improve the quality of the images generated.Breaking down creative barriers: When you're stuck for ideas, this feature can help you find new inspiration.5. Actual effectsBy using the prompt extension, you can achieve the following effects:Generate more diverse images: Increase the variety of images generated from the original prompt.Improved accuracy: With more specific and detailed prompts, you can easily generate images that are closer to your expectations.Save time: You can avoid the trouble of manually trying out prompts.*Summary*As you can see, the tensor.art Enhance Prompt is a powerful tool that can further stimulate your creativity and streamline the image generation process. Give it a try and see the effects for yourself!!!

[Updated on October 26th]Hello everyone, this time I will briefly explain his LoRA creation feature in TensorArt. This feature allows you to create your own learning files.⚠️As I am self-studying, I would appreciate it if you could read this for reference only⚠️overview:LoRA (low rank adaptation) is an efficient method for fine-tuning AI models. TensorArt allows you to easily create your own training files with specific styles and characteristics using LoRA. This allows you to generate images for individual projects and creative needs.process:1. Login and menu selection:First, log into TensorArt and select the Online Training option from the menu.2. Upload images:Add the images you want to train to the upload area on the left. To do this, prepare multiple images with specific characteristics, such as the character's expression or pose.3. Set model and trigger word:Select the model theme to be used, the base model (select from first, anime, reality, 2.5D, standard, custom), and set the trigger word etc.🌸 If you select Custom, you can now train using your favorite base model (SDXL, SD3, Hanyuan, FLUX).🌸Trigger words do not necessarily need to be set depending on the purpose.4. About tags:Tags are automatically generated for each image when you upload it. Click on the uploaded image to check, delete, or add the generated tags. By deleting the tags of the features you want to learn, you can learn the features more accurately. Adjusting the tags will improve the quality of the images produced.(If this is your first time, feel free to ignore it.)5. Run the training:Once the settings are complete, click the "Train Now" button at the bottom right. Training can take minutes to hours, and you can track your progress on a dedicated page. The amount of credits consumed will vary depending on the number of images you prepare, the number of training sessions, and the number of epochs, so please proceed in a planned manner.6. Download the file:Once training is complete, download the generated LoRA file and use it for actual image generation.7. Host the model:Proceed to create a project from "Host my model", enter the necessary information and click the create button.Completion and testing:Let's try image generation using the trained LoRA file. Although features can be learned sufficiently with a small number of images, similar compositions and poses are more likely to be generated if there are fewer reference images.　　　　　　　　　　　　　Completed: "Shizuku-chan" general-purpose XLCredit consumption:Creating LoRA consumes credits. The number of credits consumed varies depending on the number of images you prepare, the number of training sessions, and the number of epochs, so it is important to check the number of credits you need in advance and proceed accordingly. If you don't have enough credits, we recommend purchasing more or considering a Pro plan.summary:By using TensorArt's LoRA creation function, you can create illustrations with a higher degree of freedom. Please try out the features that are easy to use even for beginners. By using LoRA, your creative projects will be even more fulfilling.Let's create! !

introduction{{For those who are about to start AI image generation}}In recent years, advances in AI technology have brought about revolutionary changes in the field of image generation. In particular, AI-powered illustration generation has become a powerful tool for artists and designers. However, as this technology advances, issues of creativity and copyright arise. In this article, we will explain the possibilities of AI image generation, specific use cases, how to create prompts, how to use LoRA and its effects, keywords for improving image quality, consideration for copyright, etc.Fundamentals of AI image generationAI image generation uses artificial intelligence to learn from data and generate new images. Deep learning techniques are often used for this, and one notable approach is stable diffusion. Stable Diffusion employs a probabilistic method called a diffusion model to gradually remove noise during image generation, resulting in highly realistic, high-quality output.Generating real imagesAI technology is excellent not only for creating cute illustrations, but also for generating realistic images. For example, you can generate high-resolution images that resemble photorealistic landscapes or portraits. By utilizing Stable Diffusion, it is possible to generate more detailed images, which expands the possibilities of application in various fields such as advertising, film production, and game design.Generate cute illustrationsOne of the practical applications of AI image generation is the creation of cute illustrations. This is useful for things like character design and avatar creation, allowing you to quickly generate different styles. This process typically involves collecting a large dataset of illustrations, training an AI model on this data to learn different styles and patterns, and generating new illustrations based on user input or keywords.creativity and AIAI image generation also influences creative ideas. Artists can use her AI-generated images as inspiration for new works or expand on ideas, which can lead to the creation of new styles and concepts never thought of before.Use and effects of LoRALoRA (Low-Rank Adaptation) is a technique used to improve the performance of AI models. Its impacts include:1. Fine-tune models: LoRA allows you to fine-tune existing AI models to learn specific styles and features, allowing for customization based on user needs.2. Efficient learning: LoRA reduces the need for large-scale data collection and training costs by efficiently training models using small datasets.3. Rapid adaptation: LoRA allows you to quickly adapt to new styles and trends, making it easy to generate images tailored to your current needs.For example, LoRA can be leveraged to efficiently achieve high-quality results when generating illustrations in a specific style.Creating a promptWhen instructing an AI to generate illustrations, it's important to create effective prompts. Key points for creating prompts include providing specific instructions, using the right keywords, trial and error, and an optional reference image to help the AI figure out what you're looking for. Keywords for improving image qualityWhen creating prompts for AI image generation, you can incorporate keywords related to image quality improvement to improve the overall quality of the images generated. Useful keywords include "high resolution," "detail," "clean lines," "high quality," "sharp," "bright colors," and "photorealistic."Copyright considerationsImage generation using AI also raises copyright issues. If the dataset used to train your AI model contains copyrighted works, the resulting images may infringe your copyright. When using AI image generation tools, it's important to be aware of the data source, ensure that the generated images comply with copyright laws, and check the license agreement.conclusionAI image generation offers great possibilities for artists and designers, but it also raises challenges related to copyright. By using data responsibly and understanding copyright law, you can leverage AI technology to create innovative work. Leveraging technologies like LoRA can further improve efficiency and quality. Users can adjust the output by incorporating image enhancement keywords into the prompt. Let's explore new ways of expression while being aware of advances in AI technology and the considerations that come with it! !