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-500/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-500/pytorch_lora_weights.bin
- Command line
-
hf download hf://lora-library/ameersGenerativeModel@f7ad409cdb8f25fc94a18dca6cdad9e665a367a9/checkpoint-500/pytorch_lora_weights.bin
-
curl -L -o pytorch_lora_weights.bin https://huggingface.co/lora-library/ameersGenerativeModel/resolve/f7ad409cdb8f25fc94a18dca6cdad9e665a367a9/checkpoint-500/pytorch_lora_weights.bin
3.29 MB
- Xet hash:
- 65d6b4e9a2c54242ee84b3773e17931033d528b9fa3229168b7bad619b1af34e
- Size of remote file:
- 3.29 MB
- SHA256:
- 9a53425fb92664bc18e7195c0f7311ce1ecf6496593513f5832a7cb0182acb15
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