Instructions to use Lonuhbow/makeout2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lonuhbow/makeout2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Lonuhbow/makeout2") prompt = "Makeout2" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 1,351 Bytes
c21c636 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | {
"step": 2000,
"scores": [
{
"case": 1,
"seed": 1009,
"score": null,
"observed": null
},
{
"case": 1,
"seed": 2003,
"score": null,
"observed": null
},
{
"case": 2,
"seed": 1009,
"score": null,
"observed": null
},
{
"case": 2,
"seed": 2003,
"score": null,
"observed": null
},
{
"case": 3,
"seed": 1009,
"score": null,
"observed": null
},
{
"case": 3,
"seed": 2003,
"score": null,
"observed": null
},
{
"case": 4,
"seed": 1009,
"score": null,
"observed": null
},
{
"case": 4,
"seed": 2003,
"score": null,
"observed": null
},
{
"case": 5,
"seed": 1009,
"score": null,
"observed": null
},
{
"case": 5,
"seed": 2003,
"score": null,
"observed": null
},
{
"case": 6,
"seed": 1009,
"score": null,
"observed": null
},
{
"case": 6,
"seed": 2003,
"score": null,
"observed": null
}
],
"mean": null,
"criteria": {
"count_match": null,
"position_match": null,
"roles_match": null,
"action_match": null,
"anatomy_ok": null
},
"scored_images": 0
}
|