Instructions to use mcurmei/unique_N_max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcurmei/unique_N_max with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mcurmei/unique_N_max")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mcurmei/unique_N_max") model = AutoModelForQuestionAnswering.from_pretrained("mcurmei/unique_N_max") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03dda951b72f510fd4d9c70bcd23f8de1b0e3cdab662150994c81c54cf735cee
- Size of remote file:
- 3.06 kB
- SHA256:
- e2441e07f4d055319c29583ea5bbcce1c94e8f2b681506033b9adab6ae635512
路
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