Instructions to use coversia21/RVC_DocTops with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use coversia21/RVC_DocTops with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("h94/IP-Adapter-FaceID", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("coversia21/RVC_DocTops") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 379 Bytes
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tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '-'
output:
url: images/Captura de pantalla 2023-12-25 191107.png
base_model: h94/IP-Adapter-FaceID
instance_prompt: null
license: openrail
---
# RVC_DocTops
<Gallery />
## Download model
[Download](/coversia21/RVC_DocTops/tree/main) them in the Files & versions tab.
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