Instructions to use inclusionAI/Ming-Image-0.1-Design with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
Add vLLM-Omni deployment links
Browse files
README.md
CHANGED
|
@@ -49,6 +49,13 @@ For transparent-background generation, prepend exactly one of the recommended
|
|
| 49 |
RGBA phrases. See the
|
| 50 |
[transparent-background generation tip](https://github.com/inclusionAI/Ming-Image#transparent-background-generation-tip).
|
| 51 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 52 |
## Recommended settings
|
| 53 |
|
| 54 |
- Resolution: **2048 x 2048** (recommended), or **1024 x 1024** for faster
|
|
|
|
| 49 |
RGBA phrases. See the
|
| 50 |
[transparent-background generation tip](https://github.com/inclusionAI/Ming-Image#transparent-background-generation-tip).
|
| 51 |
|
| 52 |
+
## Deployment
|
| 53 |
+
|
| 54 |
+
We recommend the following inference frameworks to serve the model:
|
| 55 |
+
|
| 56 |
+
- vLLM-Omni: see the [recipes](https://github.com/vllm-project/vllm-omni/blob/main/recipes/inclusionAI/Ming-Image.md)
|
| 57 |
+
and [installation guide](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/quickstart/).
|
| 58 |
+
|
| 59 |
## Recommended settings
|
| 60 |
|
| 61 |
- Resolution: **2048 x 2048** (recommended), or **1024 x 1024** for faster
|