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
File size: 389 Bytes
8185c63 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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"
]
} |