Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use AliRiza/kramer_face with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AliRiza/kramer_face with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AliRiza/kramer_face", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of kramer person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from AliRiza/kramer_face: direct link, hf CLI and curl.
- Browser
- Download file 557 Bytes
-
https://huggingface.co/AliRiza/kramer_face/resolve/main/README.md
- Command line
-
hf download hf://AliRiza/kramer_face/README.md
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curl -L -o README.md https://huggingface.co/AliRiza/kramer_face/resolve/main/README.md
557 Bytes
metadata
license: creativeml-openrail-m
base_model: CompVis/stable-diffusion-v1-4
instance_prompt: a photo of kramer person
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- dreambooth
inference: true
DreamBooth - AliRiza/kramer_face
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of kramer person using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: True.