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
File size: 407 Bytes
44a87fd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"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"
}
|