Instructions to use xFutureTechx/2024_Backups with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xFutureTechx/2024_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/2024_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
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 767 Bytes
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license: creativeml-openrail-m
datasets:
- Duskfallcrew/Creative-Embeddings
- EarthnDusk/Embeddings_SD15
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable diffusion
- art
base_model:
- stable-diffusion-v1-5/stable-diffusion-v1-5
---
# 2023 & 2024 Post Consumer Bullshiz (Fomerly KofI Release Models)
Do's and Don'ts:
Do USE XYPHER'S Tool to find metadata! [Doro Metadata](https://xypher7.github.io/lora-metadata-viewer/)
Do NOT REUPLOAD
DO - Reuse, RECYCLE AND MERGE! - Credit, and if possible leave metadata on - not because we're a prude, but because then I can see what lovely creations you've used and how smart you are compared to me!
[Runpod](https://runpod.io/?ref=yx1lcptf)
[VastAI](https://cloud.vast.ai/?ref=70354) |