Instructions to use rdecoupes/tetis-geochallenge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rdecoupes/tetis-geochallenge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rdecoupes/tetis-geochallenge")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rdecoupes/tetis-geochallenge") model = AutoModelForTokenClassification.from_pretrained("rdecoupes/tetis-geochallenge") - Notebooks
- Google Colab
- Kaggle
TETIS Text Mining contribution to the GeoChallenge: Location Mention Recognition
This model was trained for the GeoAI Challenge organized by AIforGood and won the 2nd prize.
It takes as an input a tweet content and extracts location mentions (Name Entity Recognition task focused on spatial entity).
More information could be found in the GeoAI github repository
Authors
| Name | Github |
|---|---|
| Rémy Decoupes | @remydecoupes |
| Nejat Arinik | @arinik9 |
| Roberto Interdonato | @interdonatos |
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