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
Download training_args.bin from TweebankNLP/bertweet-tb2-pos-tagging: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/TweebankNLP/bertweet-tb2-pos-tagging/resolve/main/training_args.bin
- Command line
-
hf download hf://TweebankNLP/bertweet-tb2-pos-tagging/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TweebankNLP/bertweet-tb2-pos-tagging/resolve/main/training_args.bin
2.8 kB
- Xet hash:
- 1a4d2eff7fa05f30819853b6e39e9fc280f1d41c62fd3742b4a1c14f3f4cdc5d
- Size of remote file:
- 2.8 kB
- SHA256:
- 340b2b7da48ccf6fda460804a1a20010417e33cf466899893cbb25ffd57757f9
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