Instructions to use mdraw/german-news-sentiment-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mdraw/german-news-sentiment-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mdraw/german-news-sentiment-bert", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mdraw/german-news-sentiment-bert") model = AutoModelForSequenceClassification.from_pretrained("mdraw/german-news-sentiment-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b778317e753672dc9710f01dd74735dacc5b418d37ab1ee61a22924ba1f2951
- Size of remote file:
- 436 MB
- SHA256:
- 543e68367c47af4937ab2a34ed6ba1fd76eb8eb1f8cadefe477824d70a8042c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.