This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set: Loss: 0.1665 F1: 0.8559

Otherxlm-roberta-base

Status

AufgelistetUnrated

AnleitungSweet Tea

HiDream I1 Fast image generator: mechanisms and practical controls

Start with one image from text, follow the exact conditioning, sampling and decoding path, and configure size, starting noise and guidance with the recipe's actual controls.

Status

AufgelistetUnrated

PipeSweet Tea

PMRF image enhancer

Upload a source image to produce a PMRF-enhanced image. For a first run, keep the source defaults of 2× scale, 25 steps, and Lanczos interpolation. Scale controls enlargement; use 1× to process at the original size. Larger scales increase output dimensions and resource requirements. Steps controls the processing iteration count and trades additional computation for a different restoration result. Interpolation selects the resizing method. Seed lets you vary the result; the default randomizes on each run. This workflow has no prompt or restoration-strength control. Uploaded transparency is not preserved because only the loader's RGB image output is connected.

Upscaling1024x10248GB VRAM

Status

AufgelistetUnrated

PipeSweet Tea

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.

FLUX.2 [klein] 4B1024x10248GB VRAM

Status

AufgelistetUnrated

ModellExterne Quelle

[SDXL] FLYX3_MIX (AnimagineXL31)

Krea2_Turbo_Exciter_HR_Workflow

Stepping up one feature set. This is still simple but has wildcard integration. So can slowly learn how to amplify you ComfyUI.

FLUX virtual try-on: mechanisms and practical controls

Create a try-on preview from a person photo and one garment reference, configure the actual styling and seed inputs, and understand the provider path and preservation limits.

Status

AufgelistetUnrated

ModellExterne Quelle

DnD Darkest Fantasy

【FLUX】INPAINT — v3.1

Optimize for 1080p screen and some correction

Sprite sheet generator. — Frist and Last v1.1

This workflow automates the conversion of a single sprite image into game-ready assets. It uses Wan 2.2 to generate a smooth, looping animation from a reference image, then extracts a specific number of frames to...