Instructions to use tm-hf-repo/tmbd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tm-hf-repo/tmbd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tm-hf-repo/tmbd") prompt = "tmbd" 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("undefined", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("tm-hf-repo/tmbd")
prompt = "tmbd"
image = pipe(prompt).images[0]tmbd
Model description
seedream prompt was: * make this bande dessinée cartoon style, very detailed face and hair,
Trigger words
You should use tmbd to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
INPUT
WITH TRIGGER PROMPT
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