Instructions to use Jundot/GLM-5.3-Flash-oQ4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Jundot/GLM-5.3-Flash-oQ4e with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir GLM-5.3-Flash-oQ4e Jundot/GLM-5.3-Flash-oQ4e
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| { | |
| "image_processor": { | |
| "do_rescale": true, | |
| "patch_expand_factor": 1, | |
| "merge_size": 2, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "temporal_patch_size": 2, | |
| "patch_size": 14, | |
| "min_image_tokens": 16, | |
| "max_image_tokens": 8000, | |
| "image_processor_type": "Glm5NextImageProcessor" | |
| }, | |
| "video_processor": { | |
| "do_rescale": true, | |
| "video_processor_type": "Glm5NextVideoProcessor", | |
| "patch_expand_factor": 1, | |
| "merge_size": 2, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "temporal_patch_size": 2, | |
| "patch_size": 14, | |
| "min_image_tokens": 16, | |
| "max_image_tokens": 240000, | |
| "fps": 2 | |
| }, | |
| "processor_class": "Glm5NextProcessor" | |
| } | |