Instructions to use zeromodels/dfine-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/dfine-medium 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/dfine-medium") - Keras
How to use zeromodels/dfine-medium 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/dfine-medium") - Notebooks
- Google Colab
- Kaggle
File size: 519 Bytes
f5aec8e 680647b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"library_name": "zeromodels",
"zeromodels_version": "1.1.3",
"preprocessor_module": "zeromodels.models.dfine",
"preprocessor_class": "DFineImageProcessor",
"variant": "dfine-medium",
"size": {
"height": 640,
"width": 640
},
"resample": "bilinear",
"do_rescale": true,
"rescale_factor": 0.00392156862745098,
"do_normalize": false,
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"return_tensor": true,
"data_format": null
} |