Token Classification
GLiNER
PyTorch
English
NER
GLiNER
information-extraction
entity-recognition
biomed
biological-entities
disease
chemical
gene
variant
species
cell-line
biored
Instructions to use anthonyyazdaniml/gliner-biomed-large-v1.0-disease-chemical-gene-variant-species-cellline-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use anthonyyazdaniml/gliner-biomed-large-v1.0-disease-chemical-gene-variant-species-cellline-ner with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("anthonyyazdaniml/gliner-biomed-large-v1.0-disease-chemical-gene-variant-species-cellline-ner") - Notebooks
- Google Colab
- Kaggle
gliner-biomed-large-v1.0-disease-chemical-gene-variant-species-cellline-ner / special_tokens_map.json
| { | |
| "bos_token": { | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "cls_token": { | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eos_token": { | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "mask_token": { | |
| "content": "[MASK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "[PAD]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "sep_token": { | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "unk_token": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |