Instructions to use MiMe-MeMo/Dialogue_dfm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MiMe-MeMo/Dialogue_dfm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MiMe-MeMo/Dialogue_dfm")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MiMe-MeMo/Dialogue_dfm") model = AutoModelForTokenClassification.from_pretrained("MiMe-MeMo/Dialogue_dfm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccc6bce3b3c8b9fa7bc939760a9136c175d753a55ce0b61d6340b143642d6b0b
- Size of remote file:
- 5.24 kB
- SHA256:
- 074b9f52bb57b9c68f0f2260d2e40fcb63a34ab6b6314af5c5f4f91facaf7c02
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