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
File size: 455 Bytes
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pipeline_tag: image-segmentation
license: mit
library_name: kerasformers
tags:
- keras
- kerasformers
- eomt
- tf
- jax
- pytorch
---
# eomt_large_coco_instance_640 (Keras 3)
Pure-Keras 3 weights for [kerasformers](https://github.com/IMvision12/KerasFormers), mirrored from the source. License: `mit`.
```python
from kerasformers.models.eomt import EoMTUniversalSegment
model = EoMTUniversalSegment.from_weights("eomt_large_coco_instance_640")
```
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