Instructions to use Outer-Spatial/nathan2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Outer-Spatial/nathan2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Outer-Spatial/nathan2") prompt = "abbeyy" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit ·
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Parent(s): 2325b23
saving checkpoint-200
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README.md
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# LoRA DreamBooth - Outer-Spatial/nathan2
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## MODEL IS CURRENTLY TRAINING ...
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Last checkpoint saved: checkpoint-
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These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
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The weights were trained on the concept prompt:
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```
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# LoRA DreamBooth - Outer-Spatial/nathan2
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## MODEL IS CURRENTLY TRAINING ...
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Last checkpoint saved: checkpoint-200
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These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
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The weights were trained on the concept prompt:
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```
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checkpoint-200/optimizer.bin
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size 14989511
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checkpoint-200/pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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size 23401064
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checkpoint-200/random_states_0.pkl
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version https://git-lfs.github.com/spec/v1
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size 14599
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checkpoint-200/scaler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:4fccf0f9be1bb8f24861e4393745b3e09cc2687125a69e3757955fb0f0925ea5
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size 557
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checkpoint-200/scheduler.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d2565f1f317aadcb95557955732a7a05efb023cacf90620d89fcb0c7ac0f8e04
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size 563
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