Instructions to use Fred99774/kalssanew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Fred99774/kalssanew with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Fred99774/kalssanew", 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 Fred99774/kalssanew: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/Fred99774/kalssanew/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Fred99774/kalssanew/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Fred99774/kalssanew/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 3553b0ef8240aaba839f0b0c446ba7aa3837e07c6028c6960a0b3f3e2c1caa6b
- Size of remote file:
- 246 MB
- SHA256:
- 3d3f17ebbaea6a2401331d6f7da6380a133c2fae4bb8d2ddfd96152f083fb087
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