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
| 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) |