Instructions to use AMR-KELEG/Sentence-ALDi-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMR-KELEG/Sentence-ALDi-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AMR-KELEG/Sentence-ALDi-50")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AMR-KELEG/Sentence-ALDi-50") model = AutoModelForSequenceClassification.from_pretrained("AMR-KELEG/Sentence-ALDi-50") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (f3b34ee49063b22a0333bd4a00e2deed2329d8ee)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
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