Instructions to use ficsort/bert-large-uncased-conll2003-pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ficsort/bert-large-uncased-conll2003-pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ficsort/bert-large-uncased-conll2003-pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ficsort/bert-large-uncased-conll2003-pos") model = AutoModelForTokenClassification.from_pretrained("ficsort/bert-large-uncased-conll2003-pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f939e5bcc40777301c8dbb1374011bdf34fa597201c1118e15f01398e71b65f9
- Size of remote file:
- 1.34 GB
- SHA256:
- 6df1455a6db7ec7a51725fed6a0efd78bc23c195ed7d4784139955968d61fd3e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.