Instructions to use Amir13/xlm-roberta-base-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 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")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Amir13/xlm-roberta-base-de-base-ner") model = AutoModelForTokenClassification.from_pretrained("Amir13/xlm-roberta-base-de-base-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23c56fc56ac6fa4a1474091fae7b60ab9dcf2c1fc00292f9678665b9ecd755ab
- Size of remote file:
- 1.11 GB
- SHA256:
- e8ca433db3a79c605ee3a72a86db5659f676fbfe7a557e838ca605db5912edc5
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