Instructions to use mcurmei/single_label_N_max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcurmei/single_label_N_max with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mcurmei/single_label_N_max")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mcurmei/single_label_N_max") model = AutoModelForQuestionAnswering.from_pretrained("mcurmei/single_label_N_max") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c818661cf11eafc65fc0eba12ea0ee8e4cb2345b0bc4d053c0cd659f5095946e
- Size of remote file:
- 3.06 kB
- SHA256:
- 4bc4a01f1657e1555b0d3bef56a8205787216ad588247496ff12803de2428be7
路
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