Instructions to use kellempxt/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kellempxt/checkpoints with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kellempxt/checkpoints", 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
Upload sdxl/copyGodiva/technical_info.json with huggingface_hub
Browse files
sdxl/copyGodiva/technical_info.json
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{
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"file_size_bytes": 6938040682,
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"file_size_mb": 6616.63,
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"network_type": null,
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"rank": null,
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"alpha": null,
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"base_model_type": null,
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"resolution": null,
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"num_train_images": null,
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"num_epochs": null,
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"num_tensors": 2515,
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"tensor_dtypes": [
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"F16"
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]
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}
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