Instructions to use himmug/himanshu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use himmug/himanshu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("himmug/himanshu", 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
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Upload sample_images with huggingface_hub
f18492e -
Upload model_index.json with huggingface_hub
a4565ca -
Upload vae with huggingface_hub
9ed3c77 -
Upload unet with huggingface_hub
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Upload tokenizer with huggingface_hub
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Upload text_encoder with huggingface_hub
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Upload scheduler with huggingface_hub
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Upload feature_extractor with huggingface_hub
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Upload the concept himanshu embeds and token
f024528 -
initial commit
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