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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b2005ea2e87c4ac740dec547c7968189293b8272c595669a9ed89cf6f65a8a0
- Size of remote file:
- 993 MB
- SHA256:
- 2e61e5b1d6d6fee16d27cbc243a8d1d18a5d3738669dbb2facbbd2018e96360e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.