Instructions to use dataautogpt3/TempestV0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dataautogpt3/TempestV0.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dataautogpt3/TempestV0.1", dtype=torch.bfloat16, device_map="cuda") prompt = "Food photography style photo RAW,piece of fried grilled meat, splashes of ketchup and mustard sauce, (rosemary), spices, exceptional shallow depth-of-field capabilities, atmospheric haze blur,vivid colors,high quality textures of materials, volumetric textures, coating textures, metal textures . Appetizing, professional, culinary, high-resolution, commercial, highly detailed" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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@@ -32,15 +32,13 @@ What is the diffrence between Base and Artistic?
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Base is the pure 100% trained model without any special loras or models throw into the mix.
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suggested settings for
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cfg: 7 to 8
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steps: 60 to 80
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Artistic is less overall cohesive at larger sizes but has much more flare and stylistic promise. (Proteus+Tempest=Artistic Tempest)
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suggested settings for
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cfg: 3
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steps: 60 to 80
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both of these checkpoints have there place and are seperate for ease of understanding for the user.
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Base is the pure 100% trained model without any special loras or models throw into the mix.
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suggested settings for Base are:
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cfg: 7 to 8
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steps: 60 to 80
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Artistic is less overall cohesive at larger sizes but has much more flare and stylistic promise. (Proteus+Tempest=Artistic Tempest)
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suggested settings for Artistic are:
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cfg: 3
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steps: 60 to 80
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both of these checkpoints have there place and are seperate for ease of understanding for the user.
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