Instructions to use OneclickAI/RNN_test_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use OneclickAI/RNN_test_Model 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://OneclickAI/RNN_test_Model") - Notebooks
- Google Colab
- Kaggle
File size: 500 Bytes
9a24bb1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"model_type": "SimpleRNN_for_Sequence_Classification",
"embedding_layer": {
"input_dim": 10000,
"output_dim": 32
},
"rnn_layer": {
"type": "SimpleRNN",
"units": 32
},
"classifier_head": {
"units": 1,
"activation": "sigmoid"
},
"preprocessing": {
"max_sequence_length": 256,
"padding_type": "pre"
},
"training_details": {
"loss_function": "binary_crossentropy",
"optimizer": "adam",
"metrics": ["accuracy"]
}
} |