Instructions to use umanlp/babelbert-ft-xlm-r with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use umanlp/babelbert-ft-xlm-r with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="umanlp/babelbert-ft-xlm-r")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("umanlp/babelbert-ft-xlm-r") model = AutoModel.from_pretrained("umanlp/babelbert-ft-xlm-r", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13d76e1151c73dd8f0b52bca5d56295bcdac58690df62b36e5bc6d708afaa20b
- Size of remote file:
- 1.11 GB
- SHA256:
- 455715dc2619fec8c269c17df4396d9ae7b9e87e48b7229993cb34b814f14aae
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