Instructions to use doa12/remove_new_train_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use doa12/remove_new_train_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("doa12/remove_new_train_lora", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download checkpoint-10000/optimizer.bin from doa12/remove_new_train_lora: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/doa12/remove_new_train_lora/resolve/main/checkpoint-10000/optimizer.bin
- Command line
-
hf download hf://doa12/remove_new_train_lora/checkpoint-10000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/doa12/remove_new_train_lora/resolve/main/checkpoint-10000/optimizer.bin
6.59 MB
- Xet hash:
- 84846d5a28bb3c0275fe0b4ebfb277dc681e366a71934477075b40d8f5f215a6
- Size of remote file:
- 6.59 MB
- SHA256:
- dbf29eec785904546f99e2cee7c2aef6853369d81b5bc6e74b15f0275756ecbb
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