Instructions to use RashidNLP/German-Text-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RashidNLP/German-Text-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RashidNLP/German-Text-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RashidNLP/German-Text-Classification") model = AutoModelForSequenceClassification.from_pretrained("RashidNLP/German-Text-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 304c2daf5a9716abcab33e878e1ffa4333f8f2d2b7e4e312df6c9cc0c530eb3b
- Size of remote file:
- 1.11 GB
- SHA256:
- 18164ca20f8bc930e449586e427e6388d9e95e7bbe32d8442a2152474a320d18
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