Instructions to use xFutureTechx/Backups with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xFutureTechx/Backups 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/Backups", 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: 700 Bytes
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license: creativeml-openrail-m
datasets:
- EarthnDusk/XL_PDXL_Embeddings
language:
- en
library_name: diffusers
tags:
- not-for-all-audiences
---
These are models that I found great on Shakker.AI but because their download system is insanely slow I grabbed a couple for use on A1111.
Models backed up for personal use are:
https://www.shakker.ai/modelinfo/72975eac4a6e443286eb65a1da21fad5?from=feed&versionUuid=a491fcdfe74f408a8de5e418c938edc1
https://www.shakker.ai/modelinfo/032e3558fac249da881560428cc804a2?from=feed&versionUuid=a340f6dbdb104bb6830f09e5094d42af
This is nothing against these model makers, just that I don't have credits on Shakker, and couldn't find them anywhere else.
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