Token Classification
Transformers
Safetensors
PyTorch
Baluchi
xlm-roberta
part-of-speech
pos-tagging
balochi
low-resource
universal-dependencies
shahbakhsh
Eval Results (legacy)
Instructions to use shahbakhsh/BalPOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahbakhsh/BalPOS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="shahbakhsh/BalPOS")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("shahbakhsh/BalPOS") model = AutoModelForTokenClassification.from_pretrained("shahbakhsh/BalPOS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| ,ADJ,ADP,ADV,AUX,CCONJ,DET,INTJ,NOUN,NUM,PART,PRON,PROPN,PUNCT,SCONJ,VERB,X | |
| ADJ,157,0,4,0,0,0,0,22,0,1,2,0,0,0,8,0 | |
| ADP,0,315,2,0,0,0,0,4,0,1,2,0,2,1,1,0 | |
| ADV,6,2,68,0,3,3,0,4,0,2,1,0,0,3,3,0 | |
| AUX,1,0,2,132,0,2,0,0,0,2,0,0,0,0,9,0 | |
| CCONJ,0,0,0,0,100,0,0,0,0,0,0,0,0,0,0,0 | |
| DET,4,0,1,1,0,75,0,1,3,0,7,1,0,0,0,0 | |
| INTJ,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0 | |
| NOUN,23,7,5,0,2,0,0,596,1,0,4,14,4,1,14,0 | |
| NUM,0,0,0,0,0,2,0,0,15,0,0,0,0,0,0,0 | |
| PART,4,5,5,3,0,2,0,3,0,41,0,0,0,0,0,0 | |
| PRON,0,2,1,2,0,8,0,2,0,0,162,0,0,0,1,0 | |
| PROPN,0,0,0,0,0,0,0,7,0,0,0,53,0,0,0,0 | |
| PUNCT,0,0,0,0,1,0,0,0,0,0,0,0,182,0,0,0 | |
| SCONJ,0,0,1,0,0,0,0,0,0,0,0,0,0,59,0,0 | |
| VERB,5,0,1,6,0,0,0,9,0,0,0,0,0,0,189,0 | |
| X,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 | |