Tabular Classification
TensorFlow
Keras
Transformers
English
cvdpredict
cvd_ohca_predictor
tensorflow
ohcaprediction
ohca_predictor
custom_code
Instructions to use sharktide/ohca-predictor-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use sharktide/ohca-predictor-v1 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://sharktide/ohca-predictor-v1") - Transformers
How to use sharktide/ohca-predictor-v1 with Transformers:
# Load model directly from transformers import TFAutoModel model = TFAutoModel.from_pretrained("sharktide/ohca-predictor-v1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 558 Bytes
eb95775 657f08a 14d7222 cad9916 eb95775 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"model": {
"model_dim": 128,
"num_attention_heads": 8,
"num_encoder_layers": 4,
"feedforward_dim": 256,
"dropout_rate": 0.3,
"attention_dropout_rate": 0.15,
"static_embedding_dim": 64,
"tokens_per_modality": 64,
"max_positional_encoding": 4096,
"num_survival_bins": 12,
"uncertainty_samples": 5
},
"model_type": "cvd_ohca_predictor",
"transformers_version": "5.14.1",
"auto_map": {
"AutoConfig": "configuration_ohca.OhcaConfig",
"AutoModel": "modeling_ohca.TFCVDPredictorForOHCADetection"
}
} |