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Wan 2.2 5B video generation
Generate a silent video with Wan 2.2 5B from a scene and motion description, optionally using an uploaded image to condition the opening. For a first run, leave Source image bypassed and replace the positive prompt with your scene, subject movement, visual style, and camera movement. Keep the supplied negative prompt and default 1280 × 704 dimensions, 121 frames, 24 FPS, and 20 sampling steps. These settings produce approximately five seconds of video. Seed -1 selects fresh random noise each run; use a fixed seed when comparing changes. To animate an image, enable Source image and upload an opening image. Describe the desired movement and continuation in the positive prompt. The upload connects to the opening-image input, rather than supplying a video for editing. Uploaded transparency is not preserved through the connected RGB image path. Width and height are measured in pixels and use multiples of 32. Frame counts use 4n + 1, such as 49, 81, or 121. Increasing dimensions or frame count increases generation work. FPS controls playback speed: with a fixed frame count, increasing FPS shortens the video rather than generating additional frames. Keep batch size at 1 for one sequence; larger batches still feed one video output and do not provide separate video files. The negative prompt discourages unwanted content and artifacts. Advanced Sampling and Noise schedule controls change the denoising process; begin with their supplied defaults and denoise 1. Lower denoise is not a direct opening-image fidelity control. Use 8-bit video for broader playback compatibility. The 10-bit option requires compatible encoding and players. Advanced Video output controls select container, codec, and compression quality. Start with automatic file type and codec and quality -1; explicit encoding choices must be compatible. Encoding quality affects compression, not generated scene content. The output has no audio, even when the prompt describes music or sounds.
SCG Embedding Toolkit for Version 1.5 Models - A collection of tools and helpers from my personal kit
Over the last 6 months, I've created quite the collection of helper and tool embeds for doing things like fixing faces, pushing realism, creating anime scenes, making subjects smile, or cry, or face the camera,...
SoCalGuitarist Cinema768 Embeddings - Digital / Analog / Classic B&W - Easy movie scenes for 2.X Models!
These are another batch of high quality SD model 2.X embeddings that I am excited to release to the stable diffusion community! My new Cinema768 embeddings deliver easy cinematic lighting, color grading and...
bad_pictures
A very versatile negative embedding that helps generate high quality images. Higher chances of producing normal looking hands in realistic images.
Flux 2 Klein four-step text to image
Create images from a text description using the fixed distilled Flux 2 Klein 4B model. For a first run, replace the example Positive prompt with your subject, setting, composition, lighting and desired visual style. No uploaded image is required. Keep the source defaults: 1024 × 1024 pixels, one image, four steps, CFG 1 and Euler sampling. Run the Pipe to receive the generated image in Sweet Tea. Width and height set both the image canvas and the resolution used by the sampling schedule. Enter positive multiples of 16, at least 16 pixels. Together they determine the aspect ratio. Images per run generates a batch with the same prompt and dimensions; larger dimensions and batches require more memory. Seed -1 selects fresh random starting noise each run. Use a fixed nonnegative seed to compare changes with the same starting noise. Advanced controls expose steps, CFG and sampler. Steps set the sampling iteration count; additional steps add computation and do not guarantee better results. Keep four steps and Euler for the source setup. Changing the sampler can change results and interact with the step count. CFG adjusts positive conditioning relative to zeroed conditioning. Keep 1 for the source setup; higher values change that guidance. This branch has no editable negative prompt. This Pipe generates only the distilled-model branch's images. The separate Klein Base model with editable negative prompting belongs to the sibling tool and is not a selectable mode here. The runtime requires flux-2-klein-4b.safetensors in diffusion_models, qwen_3_4b.safetensors in text_encoders, and flux2-vae.safetensors in vae. These model dependencies are fixed. The output transport returns images to Sweet Tea without permanently saving them through ComfyUI.
Kling motion transfer
Animate a character image using movement and expressions from a reference video, returning one generated video. For a first run, upload a character image and a 3–10 second motion reference video. Keep Orientation source set to video, replace the example Scene prompt with your character, setting and desired details, then run the Pipe. With video orientation, movement, expressions, camera motion and character orientation follow the reference video; supported reference duration is 3–30 seconds. With image orientation, movement and expressions still follow the video, character orientation follows the image, and camera details come from your prompt; supported reference duration is 3–10 seconds. Keep reference audio determines whether the motion video's original sound is retained and is enabled by default. Generation mode offers pro and std, while Model version offers kling-v3 and kling-v2-6. Defaults are pro and kling-v3; the supplied source does not establish quality or performance differences between these choices. Advanced Video output settings let you choose a file type and codec; both default to automatic selection. The CRF encoding control defaults to -1, and its codec-dependent behavior is not documented in the supplied evidence. Generation uses the Kling provider and transfers the reference media for a provider-priced request. Uploaded image transparency is not preserved because only the loader's IMAGE output is connected.
Styled logo rotation
Generate a styled logo animation from a logo image and a material or matcap reference. The material reference is resized and padded to the logo's dimensions, then both images guide generation of a styled first frame. Gemini 2.5 Flash Image generates the last frame from that first frame, and Seedance animates between the two generated endpoints. For a first run, upload both required images and keep the default prompts and five-second duration. These request a studio-lit logo, a matching back view, and a 180-degree rotation. Prepare the logo's background before uploading: uploaded transparency is not carried through the connected RGB image inputs. In the styling prompt, image 1 is the logo and image 2 is the material reference. In the last-frame prompt, image 1 is the generated styled first frame. To change the movement, edit the last-frame and motion prompts together so the destination view agrees with the requested motion. Fixed camera adds a stationary-camera instruction; the default motion prompt also explicitly requests a static camera. If you want camera movement, disable Fixed camera and revise that prompt. First-frame model selects gemini-3-pro-image-preview or Nano Banana 2 (Gemini 3.1 Flash Image). First-frame shape and resolution govern the initial image; the last frame defaults to matching its shape. Video shape and resolution govern the final clip independently. Duration is 3–12 seconds. Generate audio applies only to the Seedance 1.5 Pro model. AI watermark requests a watermark from the video service. Reference preparation offers white or black padding and a resampling method. Video export offers container and codec choices; keep their Auto defaults for a first run. Both endpoint images are generated on every run; uploaded endpoint frames are not supported. Each generation stage has its own seed: -1 randomizes that stage. Fixing only the video seed does not fix the generated endpoints. Fixed Gemini seeds request best-effort repeatability rather than deterministic results. Geometry, lettering, material consistency, and camera stability are not guaranteed. The selected result is the video; model text responses are not connected to an output.
FlashVSR video upscale
Upscale an uploaded video to 720p, 1080p, 2K, or 4K with WaveSpeed FlashVSR and return one processed video. For a first run, upload your source video, keep Target resolution at 1080p, and leave File type and Codec on auto. Run the Pipe to receive the upscaled video. The uploaded video is sent to WaveSpeed for processing through a paid provider call. Target resolution controls the FlashVSR request. Under advanced Video output settings, choose auto, MP4, MKV, or WebM for the container and auto, H.264, or AV1 for the codec. These controls affect the returned video's encoding rather than the requested upscale resolution; use automatic encoding unless you need a specific format. This Pipe processes an existing video. It exposes no prompts, restoration strength, frame-rate changes, or duration controls. The source CRF default is retained as a hidden encoding setting because its behavior is not documented in the supplied evidence.
LTXvideo Image to Video refined — v4.0
This is version 4 for LTX Video 0.9.8.
赛博世界/Cyberworld/赛博朋克场景 Lora
推荐的质量词:masterpiece, best quality, score7, score8, score9, highres, extremely detailed 8k wallpaper, illustration, depth of field, great quality, amazing quality, very aesthetic, absurdres, cyberpunk, cyberpunk city,
Fashion editorial from three references
Create a fashion editorial image from separate character, background, and product references using Gemini. For a first run, upload all three required images and keep the example prompt. The references reach the model in this order: image 1 is the character and clothing, image 2 is the background, and image 3 is the product. The example requests a hard-flash, grainy editorial with the character showcasing the product. Edit the prompt's pose, expression, clothing, product placement, lighting, and film-style instructions to suit your references, then generate. Choose an explicit aspect ratio when the final layout matters; auto follows an input image's aspect ratio. Resolution defaults to 4K. The supported targets are 1K, 2K, and 4K, with Gemini's native upscaler used for 2K and 4K. Image model selects between the two source-supported Gemini models. Seed -1 randomizes each run; a fixed seed requests similar responses but does not guarantee repeatable results, especially when the model or settings change. Generation instructions set the provider's general behavior; keep their default initially and use Prompt for creative direction. Provider response can request IMAGE or IMAGE+TEXT. Only generated images are delivered by this Pipe; provider text is not connected to an output. References and prompts are sent to Gemini through a paid provider call. The result is a generative interpretation: exact identity, clothing, product details, and placement are not guaranteed. Uploaded alpha masks are not passed to generation, so uploaded transparency is not preserved by this workflow.
Stable Audio 3 audio generator
Produce MP3 audio from a text description using Stable Audio 3 Medium Base. No uploaded media is required. Describe the instruments or sound source, mood, texture, space, and desired progression; include BPM when it matters for music. For a first run, keep the supplied lo-fi description, Music category, 150-second Duration, prompt expansion enabled, and batch size 1, then generate. For an isolated hit, select One-shot and set a short Duration appropriate to its decay. Enter category values exactly as Music, Instrument, SFX, or One-shot. They select expansion instructions for the same audio generator, rather than separate generation models. Prompt expansion uses Qwen to elaborate your description. Duration sets the audio latent length independently and is converted to an integer for the expansion template. Use whole seconds to align these requests. The downstream duration input accepts 1–1000 seconds; this is an input range, not a guarantee of useful model behavior throughout that range. Category templates contain their own length suggestions, so rewritten length wording may differ from your requested Duration. Disable Expand prompt to send your description directly to audio conditioning. Category and expansion tuning then do not affect the selected prompt. Include desired tempo and length wording yourself. Expansion sampling off has a different purpose: expansion remains selected, but text generation uses no sampling. With sampling on, the expansion seed, temperature, and token selection controls affect the rewrite. Expansion token limit is measured in text tokens, not seconds. Thinking requests model-supported thinking behavior; the graph sends the resulting text directly to audio conditioning without a separate reasoning-text removal stage. Negative prompt supplies exclusion conditioning; leave it empty for the supplied default. Advanced Sampling controls the audio seed, steps, guidance, sampler, schedule, and denoising amount. Keep Denoise at the supplied 1 for full generation from an empty latent. Audio and expansion seeds are independent; -1 randomizes each run. To hold sampled expansion and audio noise choices fixed, set both seeds and retain the other settings. Audio batch controls how many duration-sized latents are sampled together. Longer clips, more steps, and larger batches increase generation work. Instrument and loop descriptions guide generation but do not guarantee isolated stems or seamless loop boundaries. MP3 quality selects V0 variable bitrate, 128k, or 320k compression and does not change the generated audio content. The source specifies stable_audio_3_medium_base.safetensors in checkpoints and t5gemma_b_b_ul2.safetensors in text_encoders from https://huggingface.co/Comfy-Org/stable-audio-3, plus qwen3.5_2b_bf16.safetensors in text_encoders from https://huggingface.co/Comfy-Org/Qwen3.5 for expansion.
Boring_e621 Negative Embedding: Enhance Images Stylistically AND Topically
This is a download site for the negative embedding boringe621. Its original huggingface repository, which goes into more detail about how it was trained and what it does, can be found here .
