Instructions to use immanuelpeter/GLM-5.3-Flash-Vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use immanuelpeter/GLM-5.3-Flash-Vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="immanuelpeter/GLM-5.3-Flash-Vision")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("immanuelpeter/GLM-5.3-Flash-Vision") model = AutoModel.from_pretrained("immanuelpeter/GLM-5.3-Flash-Vision", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from immanuelpeter/GLM-5.3-Flash-Vision: direct link, hf CLI and curl.
- Browser
- Download file 407 Bytes
-
https://huggingface.co/immanuelpeter/GLM-5.3-Flash-Vision/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://immanuelpeter/GLM-5.3-Flash-Vision/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/immanuelpeter/GLM-5.3-Flash-Vision/resolve/main/preprocessor_config.json
407 Bytes
| { | |
| "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", | |
| "processor_class": "AutoImageProcessor" | |
| } | |