Instructions to use immanuelpeter/MoonViT-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use immanuelpeter/MoonViT-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="immanuelpeter/MoonViT-V2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("immanuelpeter/MoonViT-V2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from immanuelpeter/MoonViT-V2: direct link, hf CLI and curl.
- Browser
- Download file 299 Bytes
-
https://huggingface.co/immanuelpeter/MoonViT-V2/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://immanuelpeter/MoonViT-V2/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/immanuelpeter/MoonViT-V2/resolve/main/preprocessor_config.json
299 Bytes
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_moonvit_v2.MoonViTV2ImageProcessor" | |
| }, | |
| "patch_size": 14, | |
| "merge_kernel_size": 2, | |
| "in_patch_limit": 65536, | |
| "patch_limit_on_one_side": 512, | |
| "max_num_frames": 4, | |
| "image_mean": [0.5, 0.5, 0.5], | |
| "image_std": [0.5, 0.5, 0.5] | |
| } | |