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:
- 7abbc2a7d4af7c43e0c6803ab56ce0ee550632791107fb6afb3f23e6b73e5506
- Size of remote file:
- 265 MB
- SHA256:
- d32ce4b03bf19c6f7bb22e6bd7bb42344581eb44cd0a297a54bdb455fa438d3d
路
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