Instructions to use HDKCL/izamizam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HDKCL/izamizam with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HDKCL/izamizam", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from HDKCL/izamizam: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/HDKCL/izamizam/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://HDKCL/izamizam/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HDKCL/izamizam/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 50e0e0c0967427543fb46a2a8d1ef383e75a6ae490e0d4872d79506ef8738349
- Size of remote file:
- 681 MB
- SHA256:
- ae9346e0e574ea19743e1094d395a19ea19db12c0d2f2998a3cd8c304de5d37d
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