Instructions to use Fred99774/kalssa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Fred99774/kalssa 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/kalssa", 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
Commit History
-
Upload sample_images with huggingface_hub
9660c18 -
Upload model_index.json with huggingface_hub
a43202f -
Upload vae with huggingface_hub
5d6a1fe -
Upload unet with huggingface_hub
29c655b -
Upload tokenizer with huggingface_hub
5225bed -
Upload text_encoder with huggingface_hub
2fde54f -
Upload scheduler with huggingface_hub
bc6a68b -
Upload safety_checker with huggingface_hub
1d112d4 -
Upload feature_extractor with huggingface_hub
6941812 -
Upload the concept kalssa embeds and token
f409497 -
initial commit
84f4d2b