Instructions to use lst-nectec/HoogBERTa-POS-lst20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lst-nectec/HoogBERTa-POS-lst20 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="lst-nectec/HoogBERTa-POS-lst20")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("lst-nectec/HoogBERTa-POS-lst20") model = AutoModelForTokenClassification.from_pretrained("lst-nectec/HoogBERTa-POS-lst20") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6be24198346240472dc80cc3790b6a4ad3fff34856cf7b3a3661608c975738f3
- Size of remote file:
- 572 MB
- SHA256:
- 60c52e55089ccb91765b861b7554cea6576268a0dadfc349840dd0aa1e32360c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.