Instructions to use AMR-KELEG/Sentence-ALDi-30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMR-KELEG/Sentence-ALDi-30 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AMR-KELEG/Sentence-ALDi-30")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AMR-KELEG/Sentence-ALDi-30") model = AutoModelForSequenceClassification.from_pretrained("AMR-KELEG/Sentence-ALDi-30") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
6bf737b | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:d04fb60ffb9d02de3ae35f0fec2ad0543a5704872ba9d432f2c2bf599bd00c6c
size 3515
|