Instructions to use lora-library/ameersGenerativeModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/ameersGenerativeModel 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("lora-library/ameersGenerativeModel") prompt = "gold jewelry" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/pytorch_lora_weights.bin from lora-library/ameersGenerativeModel: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/lora-library/ameersGenerativeModel/resolve/f7ad409cdb8f25fc94a18dca6cdad9e665a367a9/checkpoint-100/pytorch_lora_weights.bin
- Command line
-
hf download hf://lora-library/ameersGenerativeModel@f7ad409cdb8f25fc94a18dca6cdad9e665a367a9/checkpoint-100/pytorch_lora_weights.bin
-
curl -L -o pytorch_lora_weights.bin https://huggingface.co/lora-library/ameersGenerativeModel/resolve/f7ad409cdb8f25fc94a18dca6cdad9e665a367a9/checkpoint-100/pytorch_lora_weights.bin
3.29 MB
- Xet hash:
- 0d645a1c893164ef65a74c16e79e3d25df5296be16a3f85653423e6f79de76ec
- Size of remote file:
- 3.29 MB
- SHA256:
- 05be990e4f7dec4695724cbf2a7a5a55a38479a592dc0c5776b5687f8fd52ce5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.