Instructions to use BeePolly/cojjj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BeePolly/cojjj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("segmind/SSD-1B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("BeePolly/cojjj") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("segmind/SSD-1B", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("BeePolly/cojjj")
prompt = "-"
image = pipe(prompt).images[0]cojjj

- Prompt
- -
Model description
<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65590040b1b102df8c0b35e8/LgrDxTiIj7Q7PVUBxkgSA.mpga"></audio>
Trigger words
You should use cojjj to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for BeePolly/cojjj
Base model
segmind/SSD-1B