datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gritai-comic-pipeline
GritAI Comic Pipeline
One person. Local hardware. 13 complete AI-generated comics in a single day.
A fully local, reproducible pipeline that transforms story descriptions into complete multi-page comic books with panel layouts, character consistency, and dialogue overlays. Zero cloud APIs. Zero subscriptions. Just SDXL + Qwen + Pillow + PowerShell.
Pipeline Architecture
Story JSON → Stage 1 (SDXL Base) → Stage 2 (Qwen Edit) → Stage 3 (Pillow Assembly) → Bubble Renderer →… See the full description on the dataset page: https://huggingface.co/datasets/BonusLockSMith/gritai-comic-pipeline.flux-jungle-warrior-pipeline-v1
Flux Jungle Warrior Pipeline v1
This repository contains a complete, Flux-optimized character rendering pipeline designed for
high-consistency visual outputs using prompt engineering rather than fine-tuning.
What This Is
Curated character image datasets (PNG, metadata-scrubbed)
Flux-ready base prompts + controlled variations
ComfyUI workflow JSON
Python / PowerShell queue scripts
Prompt lessons explaining why the prompts work
This is not a trained model.This is a… See the full description on the dataset page: https://huggingface.co/datasets/BonusLockSMith/flux-jungle-warrior-pipeline-v1.bonus-one-question-pipeline
MIS 752 bonus: the whole pipeline in five cells
Optional · 50 extra credit points · about 20 minutes. Also the notebook to run when Hugging Face
is not working for you: it tests each piece and prints a report you can send Dr. Young.
Get the notebook and submit here: https://unlv.instructure.com/courses/214078/assignments/2856035
(download Bonus_One_Question_Pipeline.ipynb from this repo or from WebCampus, then in Colab: File → Upload notebook).
Five cells, top to bottom. Each… See the full description on the dataset page: https://huggingface.co/datasets/MIS-752/bonus-one-question-pipeline.s1_to_s2_bonusAdPipelineCharacterB_v1.1_ImagesAndPrompts_Pack