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-07.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-07.safetensors
- Command line
-
hf download hf://1czl66/Wisam_model/wisam_model-07.safetensors
-
curl -L -o wisam_model-07.safetensors https://huggingface.co/1czl66/Wisam_model/resolve/main/wisam_model-07.safetensors
50.9 MB
- Xet hash:
- f6d8e60a72018a58d900e4a45ae7c3d76731e46f53ecacd1692e9270727ebeb4
- Size of remote file:
- 50.9 MB
- SHA256:
- 2ba9c01c12056a8ebf77dec6b8b53ae195353b3fa02d0bdcd2f046b4e680dd4a
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