https://github.com/littlelittlecloud/torchsharp-stable-diffusion-2
https://github.com/littlelittlecloud/torchsharp-stable-diffusion-2
stable-diffusion torchsharp
Last synced: 7 months ago
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- Host: GitHub
- URL: https://github.com/littlelittlecloud/torchsharp-stable-diffusion-2
- Owner: LittleLittleCloud
- Created: 2024-03-25T21:06:42.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-16T23:29:14.000Z (almost 2 years ago)
- Last Synced: 2025-04-03T05:24:30.434Z (11 months ago)
- Topics: stable-diffusion, torchsharp
- Language: C#
- Homepage:
- Size: 1.17 MB
- Stars: 10
- Watchers: 2
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
## Torchsharp Stable Diffusion 2
This repo contains a torchsharp implementation for [stable diffusion 2 model](https://github.com/Stability-AI/stablediffusion).
## Quick Start
To run the stable diffusion 2 model on your local machine, the following prerequisites are required:
- dotnet 6
- git lfs, this is to download the model file from hugging face
### Step 1: Get the model weight from huggingface
To get stable-diffusion-2 model weight, run the following command to download model weight from huggingface. Be sure to have git lfs installed.
```bash
git clone https://huggingface.co/stabilityai/stable-diffusion-2
```
> [!Note]
> To load fp32 model weight into GPU, it's recommended to have at least 16GB of GPU memory if you want to generate 768 * 768 size image. Loading fp16 model weight requires around 8GB of GPU memory.
### Step 2: Run the model
Clone this repo and replace the `modelFolder` folder with where you download huggingface model weight in [Program.cs](./Program.cs#L25)
Then run the following command to start the model:
```bash
dotnet run
```
### Example output
(a photo of an astronaut riding a horse on mars)
### Load fp16 model weight for faster and more GPU memory efficient inference
You can load fp16 model weight by setting `dtype` to ` ScalarType.Float16` in [Program.cs](./Program.cs#L4). The inference on fp16 model weight is faster and more GPU memory efficient.
> [!Note]
> fp16 model only work with GPU because some operators doesn't work with fp16 and cpu.
### Update log
#### Update on 2024/04/03
- Add support for loading fp16 model weight
### See also
- [Torchsharp-llama](https://github.com/LittleLittleCloud/Torchsharp-llama): A torchsharp implementation for llama 2 model
- [Torchsharp-phi](https://github.com/LittleLittleCloud/Torchsharp-phi): A torchsharp implementation for phi model