Token Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
language-identification
codeswitching
Instructions to use DerivedFunction/polyglot-tagger-v2.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DerivedFunction/polyglot-tagger-v2.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DerivedFunction/polyglot-tagger-v2.2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DerivedFunction/polyglot-tagger-v2.2") model = AutoModelForTokenClassification.from_pretrained("DerivedFunction/polyglot-tagger-v2.2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5072d26aaeede75f03258041c7e5f09e63ad6de2e312db7e7de4b465df7a653b
- Size of remote file:
- 5.2 kB
- SHA256:
- 5d5d81020e6bbd67f3b2229ebb1af43c3661c83bb3947ad30ea05b011fc7aa50
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.