Instructions to use zeromodels/eomt_large_coco_instance_640 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/eomt_large_coco_instance_640 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/eomt_large_coco_instance_640") - Keras
How to use zeromodels/eomt_large_coco_instance_640 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/eomt_large_coco_instance_640") - Notebooks
- Google Colab
- Kaggle
Migrate to zeromodels (rename kf_*.json -> zm_*.json, fix refs in config + README, ensure tag + badge)
e26c715 verified | { | |
| "library_name": "zeromodels", | |
| "zeromodels_version": "1.1.3", | |
| "preprocessor_module": "zeromodels.models.eomt", | |
| "preprocessor_class": "EoMTImageProcessor", | |
| "variant": "eomt_large_coco_instance_640", | |
| "target_size": 640, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "data_format": null | |
| } |