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-6000/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-6000/optimizer.bin
- Command line
-
hf download hf://bgao95/minecraft-lora/checkpoint-6000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/bgao95/minecraft-lora/resolve/main/checkpoint-6000/optimizer.bin
3.4 MB
- Xet hash:
- 23ca4e5f87f88dbe3fbf01f406132822f466f60065c522a16764995fc365314f
- Size of remote file:
- 3.4 MB
- SHA256:
- 3d867bc68975298ebb1df86b1721f7baefffd6db2e559780fba9d9d5b6a0efd2
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