Instructions to use antonellaavad/jamie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use antonellaavad/jamie 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/jamie") prompt = "photo of jsd" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-75/custom_checkpoint_0.pkl from antonellaavad/jamie: direct link, hf CLI and curl.
- Browser
- Download file 3.42 MB
-
https://huggingface.co/antonellaavad/jamie/resolve/main/checkpoint-75/custom_checkpoint_0.pkl
- Command line
-
hf download hf://antonellaavad/jamie/checkpoint-75/custom_checkpoint_0.pkl
-
curl -L -o custom_checkpoint_0.pkl https://huggingface.co/antonellaavad/jamie/resolve/main/checkpoint-75/custom_checkpoint_0.pkl
3.42 MB
- Xet hash:
- 221d32ac321a47cfa7b6d1528502aa4d322e59087bd3473254cf66d67437ff58
- Size of remote file:
- 3.42 MB
- SHA256:
- 7811c0104d02cf9009c885ee4fab640cb5c7cbe92ff31a86c40748cb076b5a41
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