Instructions to use AlanLiJHU/MLMA_Lab5_Task5_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlanLiJHU/MLMA_Lab5_Task5_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AlanLiJHU/MLMA_Lab5_Task5_3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AlanLiJHU/MLMA_Lab5_Task5_3") model = AutoModelForTokenClassification.from_pretrained("AlanLiJHU/MLMA_Lab5_Task5_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 649b93193f8ec5ed507b84e53ed3022f75fb29db0dbd11d1240c3184a166b208
- Size of remote file:
- 4.92 kB
- SHA256:
- 6e2b086d5bbc78961f6e891667ee4d84435a67876462714097651d5e8e4d6f50
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