Instructions to use tum-nlp/neural-news-discriminator-RoBERTa-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tum-nlp/neural-news-discriminator-RoBERTa-tr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tum-nlp/neural-news-discriminator-RoBERTa-tr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tum-nlp/neural-news-discriminator-RoBERTa-tr") model = AutoModelForSequenceClassification.from_pretrained("tum-nlp/neural-news-discriminator-RoBERTa-tr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90d3df605a4adb6f74b2f5d285f472dd3ce1dbc9ff32ca77400625c02ee09e3e
- Size of remote file:
- 14.2 kB
- SHA256:
- 991e43ac880e77aebf04614d32b64496de373d179b23ef29fce160acf7668ee9
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