Instructions to use Intel/GLM-Image-int4-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/GLM-Image-int4-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Intel/GLM-Image-int4-AutoRound", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
CHANGED
|
@@ -13,7 +13,7 @@ This model is a mixed int4 model with group_size 128 and symmetric quantization
|
|
| 13 |
|
| 14 |
**Setup**
|
| 15 |
~~~bash
|
| 16 |
-
pip install git+https://github.com/
|
| 17 |
pip install git+https://github.com/huggingface/transformers.git
|
| 18 |
~~~
|
| 19 |
|
|
|
|
| 13 |
|
| 14 |
**Setup**
|
| 15 |
~~~bash
|
| 16 |
+
pip install git+https://github.com/lvliang-intel/vllm-omni.git@feats/ar-w4a16-glm-image
|
| 17 |
pip install git+https://github.com/huggingface/transformers.git
|
| 18 |
~~~
|
| 19 |
|