Image Segmentation
ZeroModels
Keras
PyTorch
JAX
TensorFlow
mobilevit
deeplabv3
semantic-segmentation
Instructions to use zeromodels/mobilevitv2_100_deeplabv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/mobilevitv2_100_deeplabv3 with ZeroModels:
# 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 zeromodels/mobilevitv2_100_deeplabv3 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/mobilevitv2_100_deeplabv3") - Notebooks
- Google Colab
- Kaggle
File size: 559 Bytes
336612f 444608a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"library_name": "zeromodels",
"zeromodels_version": "1.2.1",
"model_module": "zeromodels.models.mobilevitv2",
"model_class": "MobileViTV2SemanticSegment",
"variant": "mobilevitv2_100_deeplabv3",
"weights": "model.weights.h5",
"schema_version": 2,
"weight_dtype": "float32",
"model_type": "mobilevitv2",
"vision_config": {
"multiplier": 1.0,
"image_size": 512,
"num_classes": 21,
"output_stride": 16,
"atrous_rates": [
6,
12,
18
],
"aspp_out_channels": 512,
"aspp_dropout_prob": 0.1
}
} |