Instructions to use jayanta/roberta-harmeme-P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayanta/roberta-harmeme-P with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jayanta/roberta-harmeme-P")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jayanta/roberta-harmeme-P") model = AutoModelForSequenceClassification.from_pretrained("jayanta/roberta-harmeme-P", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e7fe159dc27e37d403feb43fbf5689c976914f20103ce731d6fcd2197809f3c
- Size of remote file:
- 499 MB
- SHA256:
- 406d5c7eef9a34c8d36c35b34043dd6c3828347f16a403ac3c18f736af38d12c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.