Instructions to use mcurmei/single_label_N_max_long_training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcurmei/single_label_N_max_long_training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mcurmei/single_label_N_max_long_training")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mcurmei/single_label_N_max_long_training") model = AutoModelForQuestionAnswering.from_pretrained("mcurmei/single_label_N_max_long_training") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35b81f79134dc4d585da589e8c7e292fe773bee0520cc9e6496495e5c5ccc72d
- Size of remote file:
- 265 MB
- SHA256:
- 16a03d10f9d6a3493a7c6c797e7227557dcccedb2571be9bc69faf491266738e
路
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