Instructions to use horsbug98/Part_2_BERT_Multilingual_Dutch_Model_E1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use horsbug98/Part_2_BERT_Multilingual_Dutch_Model_E1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="horsbug98/Part_2_BERT_Multilingual_Dutch_Model_E1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("horsbug98/Part_2_BERT_Multilingual_Dutch_Model_E1") model = AutoModelForQuestionAnswering.from_pretrained("horsbug98/Part_2_BERT_Multilingual_Dutch_Model_E1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2014920e1546cacc0e90656cb95423bef1d1ef81e992ff154c5b9e3300443bbf
- Size of remote file:
- 709 MB
- SHA256:
- 5955358b47b37565a150db40bc45824769024caf258aca40dec26618e7752c0d
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