Instructions to use AMR-KELEG/Sentence-ALDi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMR-KELEG/Sentence-ALDi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AMR-KELEG/Sentence-ALDi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AMR-KELEG/Sentence-ALDi") model = AutoModelForSequenceClassification.from_pretrained("AMR-KELEG/Sentence-ALDi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e44d2600da585b510f5295fe134b2d5556955d03863f616897d84628e19c7388
- Size of remote file:
- 3.52 kB
- SHA256:
- bbc8625719231c0cb60062ac046e1d8ffa4236ab87e5315c7b722394df689979
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