Instructions to use Violeta/ArmBERTa_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Violeta/ArmBERTa_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Violeta/ArmBERTa_Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Violeta/ArmBERTa_Model") model = AutoModel.from_pretrained("Violeta/ArmBERTa_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4a9fca9f55fe0f66d8906e1dc7e742a76af49607949743b3e0e214fdcd83a72
- Size of remote file:
- 443 MB
- SHA256:
- ce5e222f799c0849cdadca2c984f230b9c3c810c8ce265e1a2a49948f70b1c71
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