Text-to-Image
Diffusers
English
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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
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README.md
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(bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad
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legs, deformities:1.3)
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base_model:
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instance_prompt: <lora:Dall-e_3_0.3-v2-000003>
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license: mit
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language:
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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
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(bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad
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legs, deformities:1.3)
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base_model: Lykon/dreamshaper-xl-v2-turbo
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instance_prompt: <lora:Dall-e_3_0.3-v2-000003>
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license: mit
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language:
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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 Lykon/dreamshaper-xl-v2-turbo
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