Instructions to use arodriguezf/xlmr-binary-borrowings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arodriguezf/xlmr-binary-borrowings with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arodriguezf/xlmr-binary-borrowings")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arodriguezf/xlmr-binary-borrowings") model = AutoModelForTokenClassification.from_pretrained("arodriguezf/xlmr-binary-borrowings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5993578293b03ad231eec5b68b07b882682a165f2c374eea505159cc80e7a9e
- Size of remote file:
- 17.1 MB
- SHA256:
- cc02d42fb2a10276563109e2287cc0dbe6b595d5b3b3401c7cfeffc0b7e20270
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