Instructions to use kunalr63/roberta-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kunalr63/roberta-parser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kunalr63/roberta-parser")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kunalr63/roberta-parser") model = AutoModelForTokenClassification.from_pretrained("kunalr63/roberta-parser") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a27d5b49fc6aeac248b5b1297ac9395bbb1d7741bfc50906d3800c90f25fa6b
- Size of remote file:
- 497 MB
- SHA256:
- 8cb8d77a1992098856592218b302077aa5447c2eda343eb1ee368752830955bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.