Instructions to use wietsedv/xlm-roberta-base-ft-udpos28-hr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wietsedv/xlm-roberta-base-ft-udpos28-hr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wietsedv/xlm-roberta-base-ft-udpos28-hr")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-hr") model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-hr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f30a9b4cb2912e1cf3583ecb5c68a42b119f830e90b91571118293e26d5b071c
- Size of remote file:
- 1.11 GB
- SHA256:
- c95eed2cad47ebbd65290250a48a3819864352f4426eb5fd7ad23eeca952f00b
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