Instructions to use joheras/clinico with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joheras/clinico with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="joheras/clinico")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("joheras/clinico") model = AutoModelForTokenClassification.from_pretrained("joheras/clinico") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "dccuchile/distilbert-base-spanish-uncased", | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForTokenClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "dim": 768, | |
| "dropout": 0.1, | |
| "hidden_dim": 3072, | |
| "id2label": { | |
| "0": "B-DERIVED_FROM/TO", | |
| "1": "B-EVOLUTION", | |
| "2": "B-EXPLORATION", | |
| "3": "B-FAMILY_HISTORY", | |
| "4": "B-PAST_MEDICAL_HISTORY", | |
| "5": "B-PRESENT_ILLNESS", | |
| "6": "B-TREATMENT", | |
| "7": "I-DERIVED_FROM/TO", | |
| "8": "I-EVOLUTION", | |
| "9": "I-EXPLORATION", | |
| "10": "I-FAMILY_HISTORY", | |
| "11": "I-PAST_MEDICAL_HISTORY", | |
| "12": "I-PRESENT_ILLNESS", | |
| "13": "I-TREATMENT" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "B-DERIVED_FROM/TO": 0, | |
| "B-EVOLUTION": 1, | |
| "B-EXPLORATION": 2, | |
| "B-FAMILY_HISTORY": 3, | |
| "B-PAST_MEDICAL_HISTORY": 4, | |
| "B-PRESENT_ILLNESS": 5, | |
| "B-TREATMENT": 6, | |
| "I-DERIVED_FROM/TO": 7, | |
| "I-EVOLUTION": 8, | |
| "I-EXPLORATION": 9, | |
| "I-FAMILY_HISTORY": 10, | |
| "I-PAST_MEDICAL_HISTORY": 11, | |
| "I-PRESENT_ILLNESS": 12, | |
| "I-TREATMENT": 13 | |
| }, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 12, | |
| "n_layers": 6, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": true, | |
| "tie_weights_": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.27.0.dev0", | |
| "vocab_size": 31002 | |
| } | |