Token Classification
Transformers
PyTorch
Safetensors
Italian
xlm-roberta
part-of-speech
Eval Results (legacy)
Instructions to use wietsedv/xlm-roberta-base-ft-udpos28-it 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-it 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-it")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-it") model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-it") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b2e7cfe169bb22f734be5080ef100d78d46f0a74c6190b595b196ca41cb9c31
- Size of remote file:
- 1.11 GB
- SHA256:
- 1235e49452a71fcd159066553b202d5a49773310742ad181c37a8ed96e778433
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