Text-to-Image
Diffusers
English
French
Russian
stable-diffusion
lora
dalle-3
dalle
deepvision
template:sd-lora
openskyml
Instructions to use ccc8/cctec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ccc8/cctec with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lykon/dreamshaper-xl-lightning", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ccc8/cctec") prompt = "real photo of landscape of sea, skyscape, island, masterpiece, sharp details, cinematic" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
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README.md
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- openskyml
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widget:
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- text: >-
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landscape of sea, skyscape, island, masterpiece
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parameters:
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negative_prompt: >-
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(worst quality, low quality, normal quality, lowres, low details,
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pipeline_tag: text-to-image
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library_name: diffusers
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---
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- openskyml
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widget:
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- text: >-
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real photo of landscape of sea, skyscape, island, masterpiece, sharp details, cinematic
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parameters:
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negative_prompt: >-
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(worst quality, low quality, normal quality, lowres, low details,
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- ru
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pipeline_tag: text-to-image
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library_name: diffusers
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---
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copied from openskyml/dalle-3-xl
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with stablediffusionapi/juggernaut-xl-v8
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