Instructions to use ChrisZeng/twitter-roberta-base-efl-hateval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChrisZeng/twitter-roberta-base-efl-hateval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ChrisZeng/twitter-roberta-base-efl-hateval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ChrisZeng/twitter-roberta-base-efl-hateval") model = AutoModelForSequenceClassification.from_pretrained("ChrisZeng/twitter-roberta-base-efl-hateval") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e7718487d1ea14b7e0a9ccb906c2c0253de20d8d6b5083b8386b97830aefde8
- Size of remote file:
- 3.12 kB
- SHA256:
- 3966be765a13463da707bf5cd58cd4c0452776ca8eaf9c649e2dbde2a9daa7b1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.