Instructions to use zai-org/GLM-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zai-org/GLM-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zai-org/GLM-Image", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vision_language_encoder/generation_config.json from zai-org/GLM-Image: direct link, hf CLI and curl.
- Browser
- Download file 201 Bytes
-
https://huggingface.co/zai-org/GLM-Image/resolve/main/vision_language_encoder/generation_config.json
- Command line
-
hf download hf://zai-org/GLM-Image/vision_language_encoder/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/zai-org/GLM-Image/resolve/main/vision_language_encoder/generation_config.json
201 Bytes
| { | |
| "_from_model_config": true, | |
| "do_sample": true, | |
| "eos_token_id": 16385, | |
| "pad_token_id": 167855, | |
| "top_p": 0.75, | |
| "temperature": 0.9, | |
| "top_k": 16512, | |
| "transformers_version": "5.0.0dev0" | |
| } | |