Downloads · 30 days
5
2% of all-time downloads
fact_extraction_roberta_crf
apperry-ai/fact_extraction_roberta_crf
fact_extraction_roberta_crf is a token classification model from apperry-ai. Use it when you need labels on individual words, such as names. It is set up for transformers.
All-time downloads
314
Public
Repo size
993 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin496 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Sep 7, 2023
- Updated
- Sep 12, 2023
- SHA
- d7a53105
Try a prompt
Model card
From the Hugging Face model README
Supported Labels
[‘Family’, ‘Pet’, ‘Job’, ‘Likes’, ‘Dislikes’]
How to use
- Load model and perform prediction:
from tner import TransformersNER
model = TransformersNER("apperry-ai/fact_extraction_roberta")
output = model.predict(["My mom and dad is planning a big reunion next weekend"])
for entity in output['entity_prediction'][0]:
print(f"Type: {entity['type']}")
print(f"Entity: {', '.join(entity['entity'])}")
print(f"Position: {', '.join(map(str, entity['position']))}")
print(f"Probability: {', '.join(map(str, entity['probability']))}\n")
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- Created
- Sep 7, 2023
- Updated
- Sep 12, 2023