Instructions to use antonellaavad/leggregator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use antonellaavad/leggregator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("antonellaavad/leggregator") prompt = "Representative" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-900/pytorch_model.bin from antonellaavad/leggregator: direct link, hf CLI and curl.
- Browser
- Download file 3.42 MB
-
https://huggingface.co/antonellaavad/leggregator/resolve/main/checkpoint-900/pytorch_model.bin
- Command line
-
hf download hf://antonellaavad/leggregator/checkpoint-900/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/antonellaavad/leggregator/resolve/main/checkpoint-900/pytorch_model.bin
3.42 MB
- Xet hash:
- 55efc3cf56bb770b21a0fc6ccebca06e3de6e01e062f89f44b73c850dbe13a3c
- Size of remote file:
- 3.42 MB
- SHA256:
- 8f0763e73d5ab8f45b1921ddd12d3c23784d3cdcb900c8d358837a9ba3be090b
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