Instructions to use zeromodels/res2net50_26w_8s_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/res2net50_26w_8s_in1k 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/res2net50_26w_8s_in1k") - Keras
How to use zeromodels/res2net50_26w_8s_in1k 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/res2net50_26w_8s_in1k") - Notebooks
- Google Colab
- Kaggle
File size: 472 Bytes
d60066e 08cefb1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"library_name": "zeromodels",
"zeromodels_version": "1.2.1",
"model_module": "zeromodels.models.res2net",
"model_class": "Res2NetImageClassify",
"variant": "res2net50_26w_8s_in1k",
"weights": "model.weights.h5",
"schema_version": 2,
"weight_dtype": "float32",
"model_type": "res2net",
"vision_config": {
"depth": [
3,
4,
6,
3
],
"base_width": 26,
"scale": 8,
"cardinality": 1,
"num_classes": 1000
}
} |