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:
- 96eb82723bdf51b31f9ca9744dc1dc9761c861ad621776c6b919df50d8004513
- Size of remote file:
- 3.45 kB
- SHA256:
- 4a2d2533fa13078b1aefc9b2ea275e1dbbd1aff987a0bcfcad2b447f267d1895
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.