Instructions to use Amir13/bert-base-parsbert-uncased-wnut2017 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amir13/bert-base-parsbert-uncased-wnut2017 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Amir13/bert-base-parsbert-uncased-wnut2017")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Amir13/bert-base-parsbert-uncased-wnut2017") model = AutoModelForTokenClassification.from_pretrained("Amir13/bert-base-parsbert-uncased-wnut2017") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87cebb6f1f2761b45ac4f151bac0722ee8ac2506caa97623cf03fc112bd2d0f9
- Size of remote file:
- 3.52 kB
- SHA256:
- 4e216d92cfe4a7aa99de8baa541b864dbffb94035a04e310483e4910aa21e18c
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