Instructions to use guaguale/model_v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use guaguale/model_v 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("guaguale/model_v") prompt = "a photo of vvv man" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-200/optimizer.bin from guaguale/model_v: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/guaguale/model_v/resolve/main/checkpoint-200/optimizer.bin
- Command line
-
hf download hf://guaguale/model_v/checkpoint-200/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/guaguale/model_v/resolve/main/checkpoint-200/optimizer.bin
6.59 MB
- Xet hash:
- e086d2615a87d8c9636395fcd18f2a3a7da00c3193fd511bef429c1c80358ed3
- Size of remote file:
- 6.59 MB
- SHA256:
- 4081a023f52e3846b6f3ddc894c1ae7697a94dee743732fa42434e1c4103e14f
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