Instructions to use LendeaViva/roberta-punloc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LendeaViva/roberta-punloc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LendeaViva/roberta-punloc")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LendeaViva/roberta-punloc") model = AutoModelForTokenClassification.from_pretrained("LendeaViva/roberta-punloc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13c5110cfeec2090a7278492cd06ec593d7602e760dc2d2dfac6126b172eb647
- Size of remote file:
- 326 MB
- SHA256:
- e31abbd1a0432783c878e8751af018e7ac90038ad3d18fc2e11886fbb823e78b
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