Text-to-Image
Diffusers
Safetensors
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
Instructions to use ahmadmac/Images_Generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ahmadmac/Images_Generation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ahmadmac/Images_Generation", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of Ahmad, with a neatly trimmed beard and styled hair, wearing a dark green sweater and black jeans, sitting in a rustic café with a cup of tea and a notebook." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 808 Bytes
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license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
widget:
- text: a photo of Ahmad, with a neatly trimmed beard and styled hair, wearing a dark
green sweater and black jeans, sitting in a rustic café with a cup of tea and
a notebook.
---
# Model trained by ahmadmac on the ahmadmac/human dataset.
This is a Stable Diffusion model fine-tuned on my own images. It can be used by modifying the `instance_prompt`: **a photo of Ahmad **
## Description
This is a Stable Diffusion model fine-tuned on my own images.
## Usage
```python
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('ahmadmac/Images_Generation')
image = pipeline().images[0]
image
```
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