Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
protein-interactions
molecular-biology
biochemistry
systems-biology
protein
protein_complex
protein_family
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Protein-Small-166M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Protein-Small-166M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Protein-Small-166M") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-ZeroShot-NER-Protein-Small-166M
Browse files
README.md
CHANGED
|
@@ -101,7 +101,7 @@ The FSU (Florida State University) corpus is a biomedical NER dataset designed f
|
|
| 101 |
### Installation
|
| 102 |
|
| 103 |
```bash
|
| 104 |
-
pip install gliner
|
| 105 |
```
|
| 106 |
|
| 107 |
### Usage
|
|
@@ -114,7 +114,7 @@ from transformers import pipeline
|
|
| 114 |
model_name = "OpenMed/OpenMed-ZeroShot-NER-Protein-Small-166M"
|
| 115 |
|
| 116 |
from gliner import GLiNER
|
| 117 |
-
model = GLiNER.from_pretrained(
|
| 118 |
|
| 119 |
# Example usage with default entity types
|
| 120 |
text = "The Maillard reaction is responsible for the browning of many foods."
|
|
|
|
| 101 |
### Installation
|
| 102 |
|
| 103 |
```bash
|
| 104 |
+
pip install -q "gliner[tokenizers]"
|
| 105 |
```
|
| 106 |
|
| 107 |
### Usage
|
|
|
|
| 114 |
model_name = "OpenMed/OpenMed-ZeroShot-NER-Protein-Small-166M"
|
| 115 |
|
| 116 |
from gliner import GLiNER
|
| 117 |
+
model = GLiNER.from_pretrained(model_name)
|
| 118 |
|
| 119 |
# Example usage with default entity types
|
| 120 |
text = "The Maillard reaction is responsible for the browning of many foods."
|