Instructions to use Amir13/xlm-roberta-base-de-base-ner-de-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amir13/xlm-roberta-base-de-base-ner-de-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Amir13/xlm-roberta-base-de-base-ner-de-base-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Amir13/xlm-roberta-base-de-base-ner-de-base-ner") model = AutoModelForTokenClassification.from_pretrained("Amir13/xlm-roberta-base-de-base-ner-de-base-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39264e6ae2ba8e30e1cbc398cdeece730151859e33172af6a1e82a64b18805b4
- Size of remote file:
- 1.11 GB
- SHA256:
- 1fdd573f58139ff44a150675105c16ce1662c6b4a98696389da1cbc3964fcf3d
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