Text-to-Image
Diffusers
TensorBoard
lora
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use codeiceman/chicken-model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeiceman/chicken-model2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("codeiceman/chicken-model2") prompt = "I want to eat meals made of chicken" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
LoRA DreamBooth - codeiceman/chicken-model2
These are LoRA adaption weights for stabilityai/stable-diffusion-2. The weights were trained on I want to eat meals made of chicken using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for codeiceman/chicken-model2
Base model
stabilityai/stable-diffusion-2


