Instructions to use Shaer-AI/ARBERT-base-submeter-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shaer-AI/ARBERT-base-submeter-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shaer-AI/ARBERT-base-submeter-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier") model = AutoModelForSequenceClassification.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "dataset_path": "/kaggle/working/arapoems_dataverse/AraPoems_Dataset.csv", | |
| "dataset_bytes": 835101671, | |
| "dataverse_server": "https://dataverse.harvard.edu", | |
| "persistent_id": "doi:10.7910/DVN/PJPWOY", | |
| "requested_version": ":latest-published", | |
| "downloaded_directly": true, | |
| "required_columns": [ | |
| "first_hemistich", | |
| "second_hemistich", | |
| "meter", | |
| "sub_meter" | |
| ] | |
| } |