Instructions to use samanehs/test_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use samanehs/test_bert with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://samanehs/test_bert") - Keras
How to use samanehs/test_bert 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://samanehs/test_bert") - Notebooks
- Google Colab
- Kaggle
Download task.weights.h5 from samanehs/test_bert: direct link, hf CLI and curl.
- Browser
- Download file 52.8 MB
-
https://huggingface.co/samanehs/test_bert/resolve/main/task.weights.h5
- Command line
-
hf download hf://samanehs/test_bert/task.weights.h5
-
curl -L -o task.weights.h5 https://huggingface.co/samanehs/test_bert/resolve/main/task.weights.h5
52.8 MB
- Xet hash:
- 4f1123a5ef4275385c700f6b91525eafd4648d9f8a0cbba0e6b1b1674523442e
- Size of remote file:
- 52.8 MB
- SHA256:
- c841bd15c9b71aa03337e147a849c226bb21c903a1aa2a1d3de8c1dc30988c69
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