Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use bgao95/minecraft-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bgao95/minecraft-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bgao95/minecraft-lora") 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
Download checkpoint-5000/optimizer.bin from bgao95/minecraft-lora: direct link, hf CLI and curl.
- Browser
- Download file 3.4 MB
-
https://huggingface.co/bgao95/minecraft-lora/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://bgao95/minecraft-lora/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/bgao95/minecraft-lora/resolve/main/checkpoint-5000/optimizer.bin
3.4 MB
- Xet hash:
- f06114d5737a23da52477445b12b5c3fd0af8c056a42117c7a62f0ea4abbfbb0
- Size of remote file:
- 3.4 MB
- SHA256:
- 93a65341799cac76e7f2e3e51f6efacfccdf00360efeec2e04c884ea064cf0e1
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