Text-to-Image
Diffusers
lora
diffusers-training
stable-diffusion
stable-diffusion-diffusers
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
if
if-diffusers
Instructions to use talikbayev/sd_1_5_lora_26_images_white with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use talikbayev/sd_1_5_lora_26_images_white with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("talikbayev/sd_1_5_lora_26_images_white") prompt = "an image of _apusher_" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
End of training
Browse files- README.md +6 -5
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1500/optimizer.bin +3 -0
- checkpoint-1500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-1500/random_states_0.pkl +3 -0
- checkpoint-1500/scheduler.bin +3 -0
- checkpoint-500/optimizer.bin +1 -1
- checkpoint-500/pytorch_lora_weights.safetensors +1 -1
- checkpoint-500/random_states_0.pkl +1 -1
- image_0.png +0 -0
- image_1.png +0 -0
- image_2.png +0 -0
- image_3.png +0 -0
- pytorch_lora_weights.safetensors +1 -1
README.md
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- diffusers-training
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- template:sd-lora
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inference: true
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instance_prompt: an image of _apusher_
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---
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- diffusers-training
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- template:sd-lora
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- text-to-image
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inference: true
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instance_prompt: an image of _apusher_
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---
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checkpoint-1000/optimizer.bin
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