Instructions to use jhliu/ClinicalNoteBERT-tiny-simcse_sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhliu/ClinicalNoteBERT-tiny-simcse_sentence with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jhliu/ClinicalNoteBERT-tiny-simcse_sentence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 451 Bytes
7665a61 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"hidden_size": 312,
"initializer_range": 0.02,
"intermediate_size": 1200,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 2048,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 4,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"sinusoidal_pos_embds": false,
"torch_dtype": "float32",
"transformers_version": "4.16.2",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 30522
}
|