Instructions to use Kev09/Maktest2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kev09/Maktest2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/anything-v5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Kev09/Maktest2") prompt = "Hjjģhh" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/anything-v5", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Kev09/Maktest2")
prompt = "Hjjģhh"
image = pipe(prompt).images[0]Makboba1

- Prompt
- Hjjģhh
- Negative Prompt
- Hhjj
Trigger words
You should use makima \(chainsaw man\) to trigger the image generation.
You should use boba to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for Kev09/Maktest2
Base model
stablediffusionapi/anything-v5