Instructions to use 1czl66/Wisam_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 1czl66/Wisam_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("1czl66/Wisam_model") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download wisam_model-10.safetensors from 1czl66/Wisam_model: direct link, hf CLI and curl.
- Browser
- Download file 50.9 MB
-
https://huggingface.co/1czl66/Wisam_model/resolve/main/wisam_model-10.safetensors
- Command line
-
hf download hf://1czl66/Wisam_model/wisam_model-10.safetensors
-
curl -L -o wisam_model-10.safetensors https://huggingface.co/1czl66/Wisam_model/resolve/main/wisam_model-10.safetensors
50.9 MB
- Xet hash:
- 8181413c301f0c89d5055e1153a21e364c54a21d33bff5e8aa161732e2408242
- Size of remote file:
- 50.9 MB
- SHA256:
- b412ca908ce269591cedcb0a5e30b9dac1df14f74657b90b58bb37b206b55ac3
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