# stable-diffusion A latent text-to-image diffusion model with reference software for image generation and modification. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Rebuilding AUTOMATIC1111 with Gradio Workflow DevFeed: [Rebuilding AUTOMATIC1111 with Gradio Workflow]() Original publisher: [Read original article]() Author: yuvraj sharma; Abubakar Abid Published: 2026-09-10T00:00:00Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [AI Development](), [Graphs](), [stable-diffusion](), [Inference](), [Large Language Model](), [hugging face](), [vlm]() Tags: [automatic1111](), [comfyui](), [diffusion](), [flux](), [gradio](), [hugging-face](), [image-to-image](), [image-to-video](), [inference](), [inference-providers](), [llm](), [models](), [python](), [space](), [spaces](), [text-to-image](), [vlm](), [workflow](), [workflows]() ### AI overview A walkthrough of Workflow1111, a Gradio graph that recreates AUTOMATIC1111-style media pipelines with connected operator nodes for image generation, editing, prompting, and related tasks. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## How to Sell AI Prompts Online: A Step-by-Step Guide for 2026 DevFeed: [How to Sell AI Prompts Online: A Step-by-Step Guide for 2026]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-04-05T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Prompt Engineering](), [Artificial Intelligence](), [ChatGPT](), [Claude](), [stable-diffusion]() Tags: [2026](), [ai](), [chatgpt](), [claude](), [digital-products](), [guide](), [how-to](), [prompt](), [stable-diffusion]() ### AI overview A step-by-step guide to selling AI prompts online, covering prompt selection, packaging, pricing, delivery, marketplaces, and direct sales. It discusses text prompts for ChatGPT and Claude, as well as image-generation prompts for Midjourney and Stable Diffusion. ### Source excerpt Learn how to package, price, and sell AI prompts online - from ChatGPT and Midjourney prompts to full prompt libraries and subscription packs. ## Replicate Integration with Encore.ts DevFeed: [Replicate Integration with Encore.ts]() Original publisher: [Read original article]() Author: Ivan Cernja Published: 2025-11-17T00:00:00Z Content type: tutorial Language: en Sources: [Encore Updates]() Topics: [AI Development](), [text-to-image](), [API](), [flux](), [stable-diffusion](), [Node.js](), [Secrets Management]() Tags: [ai](), [api](), [diffusion](), [flux](), [integration](), [node-js](), [secrets-management](), [stable-diffusion](), [tutorial]() ### AI overview This tutorial explains how to build a type-safe backend with Encore.ts and Replicate to run AI model predictions and generate images. It covers asynchronous results, image storage, API authentication, secret management, and models such as FLUX and Stable Diffusion. ### Source excerpt Running AI models with Replicate and Encore ## Image and audio models from fal now available on DigitalOcean DevFeed: [Image and audio models from fal now available on DigitalOcean]() Original publisher: [Read original article]() Author: Grace Morgan Published: 2025-10-23T12:30:00Z Content type: release Language: en Sources: [DigitalOcean]() Topics: [AI Platform](), [Digital Ocean](), [multimodal-ai](), [API](), [stable-diffusion](), [flux](), [Serverless](), [voice ai]() Tags: [ai-platform](), [api](), [audio](), [digitalocean](), [flux](), [multimodal](), [multimodal-ai](), [product-updates](), [serverless](), [stable-diffusion]() ### AI overview DigitalOcean announces four multimodal AI models from fal in public preview on the Gradient AI Platform through Serverless Inference. The models support image generation, audio generation, and multilingual text-to-speech through an API. ### Source excerpt We're excited to announce the launch of four multimodal AI models from fal on the DigitalOcean Gradient™ AI Platform, now available in public preview through Serverless Inference. These models allow you to generate images and audio directly via API, without worrying about infrastructure, scaling, or vendor management. With this release, building AI-powered applications that include visual and audio content is easier than ever. Explore the new models The fal models, now in public preview, cover a variety of modalities, enabling you to experiment, prototype, and deploy multimodal AI features quickly: Image generation: Stable Diffusion XL fast (fal-ai/fast-sdxl) - High-resolution image generation FLUX.1 (schnell) (fal-ai/flux/schnell) - Fast image generation for quick prototyping Audio generation: Stable Audio (fal-ai/stable-audio-25/text-to-audio) - Convert text into natural-sounding audio ElevenLabs TTS Multilingual v2 9 (fal-ai/elevenlabs/tts/multilingual-v2) - Multilingual text-to-speech These models are available via Serverless Inference, letting you generate images and audio through the same simple API-driven workflow you already use on Gradient AI Platform. Try it out You can start using these models through the Serverless Inference API (https://inference.do-ai.run) after opting in to the public preview in the DigitalOcean console. Here's a quick look at how to interact with them: First, opt in to the public preview to access the fal models on the Gradient AI Platform. Once opting in, it should take about 10 to 15 minutes for your access to be granted. Example: Generate an Image export MODEL_ACCESS_KEY="YOUR_KEY" curl -sS -X POST 'https://inference.do-ai.run/v1/async-invoke' \ -H "Authorization: Bearer $MODEL_ACCESS_KEY" \ -H "Content-Type: application/json" \ -d '{ "model_id": "fal-ai/flux/schnell", "input": { "prompt": "A high-quality photo of a futuristic city at sunset" } }' Example: Generate an Image with Customized Parameters export MODEL_ACCESS_KEY="YOUR_ ## Open Preference Dataset for Text-to-Image Generation by the 🤗 Community DevFeed: [Open Preference Dataset for Text-to-Image Generation by the 🤗 Community]() Original publisher: [Read original article]() Author: David Berenstein; ben burtenshaw; Daniel Vila; Daniel van Strien; Sayak Paul; Ame Vi; Linoy Tsaban Published: 2024-12-09T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Open Source Models & Datasets](), [datasets](), [Synthetic Data Generation](), [flux](), [stable-diffusion](), [argilla](), [distilabel](), [data observability](), [GitHub](), [hugging face]() Tags: [argilla](), [artificial-intelligence](), [data](), [data-is-better-together](), [data-quality](), [datasets](), [distilabel](), [flux](), [generation](), [github](), [hugging-face](), [image](), [open](), [open-source](), [stable-diffusion](), [synthetic-data](), [synthetic-data-generation](), [text-to-image]() ### AI overview The article describes an open community effort to create an image-preference dataset for text-to-image generation. It covers prompt preparation with distilabel, synthetic data generation, image generation with Flux and Stable Diffusion, and filtering with text- and image-based classifiers plus manual review. The resulting dataset and related code are available through the Hugging Face Hub and GitHub. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Diffusers welcomes Stable Diffusion 3.5 Large DevFeed: [Diffusers welcomes Stable Diffusion 3.5 Large]() Original publisher: [Read original article]() Author: YiYi Xu; Aryan V S; Dhruv Nair; Sayak Paul; Linoy Tsaban; Apolinário from multimodal AI art; Alvaro Somoza; Aritra Roy Gosthipaty Published: 2024-10-22T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [diffusers](), [stable-diffusion](), [quantization](), [Transformer architecture](), [Optimization](), [Artificial Intelligence](), [Open Source]() Tags: [artificial-intelligence](), [diffusers](), [diffusion](), [guide](), [inference](), [memory-optimization](), [open-source](), [quantization](), [sd3-5](), [stable-diffusion](), [transformer-architecture]() ### AI overview Hugging Face introduces Stable Diffusion 3.5 Large, providing an 8B base model and a timestep-distilled variant for few-step image generation. The article explains how to use the models with Diffusers for inference and training, including gated access, memory optimization, and quantized execution for lower-memory systems. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Memory-efficient Diffusion Transformers with Quanto and Diffusers DevFeed: [Memory-efficient Diffusion Transformers with Quanto and Diffusers]() Original publisher: [Read original article]() Author: Sayak Paul; David Corvoysier Published: 2024-07-30T00:00:00Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [diffusers](), [diffusion-transformers](), [quantization](), [optimum](), [PyTorch](), [stable-diffusion](), [text-to-image](), [benchmarking]() Tags: [benchmarking](), [diffusers](), [diffusion-transformers](), [efficiency](), [gpu](), [guide](), [optimum](), [pytorch](), [quality](), [quantization](), [sd3](), [text-to-image]() ### AI overview This tutorial explains how to reduce the memory requirements of Transformer-based diffusion pipelines using Quanto quantization utilities from the Diffusers library. It benchmarks FP8 quantization on PixArt-Sigma, Stable Diffusion 3, and Aura Flow, reporting memory savings with slightly higher latency and little quality degradation. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Diffusers welcomes Stable Diffusion 3 DevFeed: [Diffusers welcomes Stable Diffusion 3]() Original publisher: [Read original article]() Author: Dhruv Nair; YiYi Xu; Sayak Paul; Alvaro Somoza; Kashif Rasul; Apolinário from multimodal AI art Published: 2024-06-12T00:00:00Z Content type: release Language: en Sources: [Hugging Face - Blog]() Topics: [stable-diffusion](), [diffusers](), [diffusion-transformers](), [Artificial Intelligence](), [text-to-image](), [multimodal](), [lora](), [Inference](), [Open Source]() Tags: [artificial-intelligence](), [diffusers](), [diffusion](), [guide](), [inference](), [lora](), [multimodal](), [open-source](), [sd3](), [stable-diffusion](), [text-to-image]() ### AI overview The article announces Stable Diffusion 3 Medium, a 2B-parameter latent diffusion model. It describes the MMDiT architecture, multimodal text and image processing, rectified flow matching, inference support through a new scheduler, and accompanying Diffusers, DreamBooth, and LoRA resources. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Launching the Artificial Analysis Text to Image Leaderboard & Arena DevFeed: [Launching the Artificial Analysis Text to Image Leaderboard & Arena]() Original publisher: [Read original article]() Author: Micah Hill-Smith; George Cameron Published: 2024-06-06T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [text-to-image](), [Human-AI evaluation](), [Artificial Intelligence](), [Open Source](), [stable-diffusion]() Tags: [artificial-intelligence](), [collaboration](), [community](), [diffusion](), [evaluation](), [generation](), [leaderboard](), [open-source](), [openai](), [ranking](), [research](), [text-to-image]() ### AI overview The Artificial Analysis Text to Image Leaderboard ranks open-source and proprietary image-generation models using ELO scores derived from more than 45,000 human image preferences. Its Image Arena uses crowdsourced comparisons across diverse prompts and use cases. The article highlights the rapid evolution of image models, the strong performance of proprietary systems, and the growing competitiveness of open-source models such as Playground AI v2.5 and Stable Diffusion 3. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Watermarks DevFeed: [Watermarks]() Original publisher: [Read original article]() Author: Adam Published: 2023-02-03T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Artificial Intelligence](), [stable-diffusion](), [Image]() Tags: [ai](), [ai-images](), [copyright](), [diffusion](), [stable-diffusion]() ### AI overview The article examines watermarks produced by diffusion image generators, arguing that these artifacts reveal how training data influences generated images. It also discusses copyright disputes involving Stable Diffusion and the ethical and economic implications of AI-generated images. ### Source excerpt Watermarks show us wierd edges of AI work