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")# pip install -U transformers accelerate # 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
Commit History
-
Update README.md
dea6cfb -
Update README.md
0216793 -
Update README.md
# 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 --> Other9af5fda -
Upload tokenizer
fb6ad9f -
Upload BertForSequenceClassification
23ce97e -
initial commit
fecf4eb