Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use cuongdev/lora-hntanh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/lora-hntanh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuongdev/test-hntanh", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("cuongdev/lora-hntanh") 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-500/optimizer.bin from cuongdev/lora-hntanh: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/cuongdev/lora-hntanh/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://cuongdev/lora-hntanh/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/cuongdev/lora-hntanh/resolve/main/checkpoint-500/optimizer.bin
6.85 MB
- Xet hash:
- f14214d02e4740ab35e0f007112f29f5011dae69f8a5077717e7880979e8f181
- Size of remote file:
- 6.85 MB
- SHA256:
- 53d41b78282002e4a91f6bb5cbb0aba47c8b9ed95904c256127e3e21c2aa0e0a
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