Instructions to use TigerHatKth/miLook with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TigerHatKth/miLook with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TigerHatKth/miLook", 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
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Download README.md from TigerHatKth/miLook: direct link, hf CLI and curl.
- Browser
- Download file 503 Bytes
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https://huggingface.co/TigerHatKth/miLook/resolve/main/README.md
- Command line
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hf download hf://TigerHatKth/miLook/README.md
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curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/TigerHatKth/miLook/resolve/main/README.md
503 Bytes
| license: gpl-3.0 | |
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| tags: | |
| - art | |
| A Lora to generate home appliance prototype in the Xiaomi Stely (Mi Look) | |
| MiLook 1.0 is good to go; | |
| MiLook 2.0 might be over trained | |
| --- | |
| with MiLook 1.0 | |
|  | |
| --- | |
| With MiLook 2.0 | |
|  |