Instructions to use kerasformers/owlv2-large-patch14-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/owlv2-large-patch14-ensemble 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/owlv2-large-patch14-ensemble 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/owlv2-large-patch14-ensemble") - Notebooks
- Google Colab
- Kaggle
File size: 458 Bytes
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pipeline_tag: zero-shot-object-detection
license: apache-2.0
library_name: kerasformers
tags:
- keras
- kerasformers
- owlv2
- tf
- jax
- pytorch
---
# owlv2-large-patch14-ensemble (Keras 3)
Pure-Keras 3 weights for [kerasformers](https://github.com/IMvision12/KerasFormers), mirrored from the GitHub release. Apache 2.0.
```python
from kerasformers.models.owlv2 import Owlv2Detect
model = Owlv2Detect.from_weights("owlv2-large-patch14-ensemble")
```
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