Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use ahbpp/ham10000-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ahbpp/ham10000-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("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ahbpp/ham10000-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-2000/optimizer.bin from ahbpp/ham10000-lora: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/ahbpp/ham10000-lora/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://ahbpp/ham10000-lora/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/ahbpp/ham10000-lora/resolve/main/checkpoint-2000/optimizer.bin
6.59 MB
- Xet hash:
- bb9abff9df22c3ec5c7f4efd785d8673e796272d06cef490beb06f2100c7382e
- Size of remote file:
- 6.59 MB
- SHA256:
- 4d22d4c0e0b53501f861050d3d3b76407c88673b15b2ec744cc6c0376560410e
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