Instructions to use TweebankNLP/bertweet-tb2-pos-tagging with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TweebankNLP/bertweet-tb2-pos-tagging with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TweebankNLP/bertweet-tb2-pos-tagging")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("TweebankNLP/bertweet-tb2-pos-tagging") model = AutoModelForTokenClassification.from_pretrained("TweebankNLP/bertweet-tb2-pos-tagging", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04dd6d56dc21e038aba2774296e35b6e746000fea85a077165b4d8aa4a0814c9
- Size of remote file:
- 537 MB
- SHA256:
- 775cfe221d7ec0024334f8edc89d41b88cc3c31a54ec19625b6eaa4e1e6ee853
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