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:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://zeromodels/eomt_large_coco_instance_640") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from zeromodels/eomt_large_coco_instance_640: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/zeromodels/eomt_large_coco_instance_640/resolve/main/model.weights.h5
- Command line
-
hf download hf://zeromodels/eomt_large_coco_instance_640/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/zeromodels/eomt_large_coco_instance_640/resolve/main/model.weights.h5
1.27 GB
- Xet hash:
- 3ac1f6e6dba8cbe977219804977f89287bada75f5fdd2c4befe3d119ab1646cb
- Size of remote file:
- 1.27 GB
- SHA256:
- fa3d365687becb307655e1881c7efbaac729dd1da433be17ac68679e7b8f81b8
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