Instructions to use kerasformers/eomt_large_coco_instance_640 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/eomt_large_coco_instance_640 with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use kerasformers/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://kerasformers/eomt_large_coco_instance_640") - Notebooks
- Google Colab
- Kaggle
| { | |
| "library_name": "kerasformers", | |
| "kerasformers_version": "1.1.3", | |
| "model_module": "kerasformers.models.eomt", | |
| "model_class": "EoMTUniversalSegment", | |
| "variant": "eomt_large_coco_instance_640", | |
| "weights": "model.weights.h5", | |
| "model_type": "eomt", | |
| "hidden_dim": 1024, | |
| "num_hidden_layers": 24, | |
| "num_heads": 16, | |
| "depths": 4, | |
| "num_queries": 200, | |
| "num_classes": 80, | |
| "layerscale_value": 1e-05, | |
| "patch_size": 16, | |
| "num_register_tokens": 4, | |
| "num_upscale_blocks": 2, | |
| "mlp_ratio": 4, | |
| "drop_path_rate": 0.0, | |
| "attention_dropout": 0.0, | |
| "use_swiglu_ffn": false, | |
| "layer_norm_eps": 1e-06, | |
| "image_size": 640 | |
| } |