Instructions to use SIRIS-Lab/actytode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIRIS-Lab/actytode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SIRIS-Lab/actytode")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SIRIS-Lab/actytode") model = AutoModelForSequenceClassification.from_pretrained("SIRIS-Lab/actytode", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 573 Bytes
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license: mit
datasets:
- SIRIS-Lab/actytode
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# ACTYTODE (ACtivity TYpe TO DEtect)
This repository provides a `bert-base-multilingual-uncased` model finetuned for ACTYTODE task based on ACTYTODE dataset, which aims at predicting organisation activity type based on the organisation legal status of the European Commission.
The activity type status for organisations are:
* PUB --> Public entity (excluding research and education)
* HES --> Higher education entity
* REC --> Research entity
* PRC --> Private company
* OTH --> Other
## Training data
## Evaluation |