Instructions to use xFutureTechx/2026_Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xFutureTechx/2026_Loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xFutureTechx/2026_Loras", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 962 Bytes
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license: creativeml-openrail-m
datasets:
- EarthnDusk/XL_PDXL_Embeddings
language:
- en
base_model:
- OnomaAIResearch/Illustrious-xl-early-release-v0
- circlestone-labs/Anima
- lodestones/Chroma1-HD
library_name: diffusers
tags:
- art
---
Original trainer didn't want to still continue with AI, and so this is a shuffle off rather than a SCRAPE.
Models won't eventualy be available other than in this repo.
However, due to the fact that the original trainer is likely to be LEAVING their posts at certain sites: Reuploading is fine.
... just for gods sakes don't link back this time LOL.
All loras are trained via: https://github.com/Ktiseos-Nyx/Ktiseos-Nyx-Trainer/
Rent Serverless GPU with VastAI: https://cloud.vast.ai/?ref_id=70354
Rent a Pod with Runpod: https://runpod.io/?ref=yx1lcptf
Railway Deployment Referral: https://railway.com/?referralCode=EQxw4P
Get Started with V0 by Vercel (NEXT/REACT AI DESIGNER): https://v0.app/ref/SI1IWJ
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