Token Classification
Transformers
Safetensors
English
bert
biomedical
named-entity-recognition
ner
biolinkbert
biored
gene
disease
variant
gdv-scout
Eval Results (legacy)
Instructions to use nobal/gdv-scout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nobal/gdv-scout with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nobal/gdv-scout")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nobal/gdv-scout") model = AutoModelForTokenClassification.from_pretrained("nobal/gdv-scout", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "task": "token_classification_ner", | |
| "scheme": "BIO", | |
| "labels": [ | |
| "O", | |
| "B-Disease", | |
| "I-Disease", | |
| "B-GeneOrGeneProduct", | |
| "I-GeneOrGeneProduct", | |
| "B-Variant", | |
| "I-Variant" | |
| ], | |
| "label2id": { | |
| "O": 0, | |
| "B-Disease": 1, | |
| "I-Disease": 2, | |
| "B-GeneOrGeneProduct": 3, | |
| "I-GeneOrGeneProduct": 4, | |
| "B-Variant": 5, | |
| "I-Variant": 6 | |
| }, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-Disease", | |
| "2": "I-Disease", | |
| "3": "B-GeneOrGeneProduct", | |
| "4": "I-GeneOrGeneProduct", | |
| "5": "B-Variant", | |
| "6": "I-Variant" | |
| }, | |
| "types": [ | |
| "Disease", | |
| "GeneOrGeneProduct", | |
| "Variant" | |
| ], | |
| "ignore_index": -100, | |
| "label_policy": "gold (BioRED); Chemical/Species/CellLine folded to O", | |
| "alignment": "char spans -> subword tokens via tokenizer offset_mapping", | |
| "source": "BioRED", | |
| "type_map": { | |
| "Gene": "GeneOrGeneProduct", | |
| "Disease": "Disease", | |
| "Variant": "Variant" | |
| } | |
| } |