Instructions to use zeromodels/mask2former-swin-tiny-coco-panoptic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/mask2former-swin-tiny-coco-panoptic with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/mask2former-swin-tiny-coco-panoptic") - Keras
How to use zeromodels/mask2former-swin-tiny-coco-panoptic with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/mask2former-swin-tiny-coco-panoptic") - Notebooks
- Google Colab
- Kaggle
| { | |
| "library_name": "kerasformers", | |
| "kerasformers_version": "1.1.3", | |
| "preprocessor_module": "kerasformers.models.mask2former", | |
| "preprocessor_class": "Mask2FormerImageProcessor", | |
| "variant": "mask2former-swin-tiny-coco-panoptic", | |
| "target_size": 384, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "data_format": null | |
| } |