File size: 1,145 Bytes
1218161 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 |
import gradio as gr
with open('materials/introduction.html', 'r', encoding='utf-8') as file:
html_description = file.read()
with gr.Blocks() as landing_interface:
gr.HTML(html_description)
with gr.Accordion("How to run this model locally", open=False):
gr.Markdown(
"""
## Installation
To use this model, you must install the GLiNER Python library:
```
pip install gliner
```
## Usage
Once you've downloaded the GLiNER library, you can import the GLiNER class. You can then load this model using `GLiNER.from_pretrained` and predict entities with `predict_entities`.
"""
)
gr.Code(
'''
from gliner import GLiNER
model = GLiNER.from_pretrained("knowledgator/gliner-multitask-large-v0.5")
text = "Your text here"
labels = ["person", "award", "date", "competitions", "teams"]
entities = model.predict_entities(text, labels)
for entity in entities:
print(entity["text"], "=>", entity["label"])
''',
language="python",
) |