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:
- 1a2930c992a965b26e169da3d95b36abb3c5dc5314fdc311866feb9830ef2e65
- Size of remote file:
- 2.99 kB
- SHA256:
- 67258a68682b4a166008b0bab5e5dc99af7887fc2e095e356a3de64c532070d4
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