Instructions to use Tanor/BERTicSENTPOS4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/BERTicSENTPOS4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/BERTicSENTPOS4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/BERTicSENTPOS4") model = AutoModelForSequenceClassification.from_pretrained("Tanor/BERTicSENTPOS4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62ee0d38943c6ad8b6e5a8fef5d81ea7740cc68ea1a58e4c63b4fbd81676a494
- Size of remote file:
- 443 MB
- SHA256:
- c04b0cf589124a0c502481443133bc5b7ac8f995b67ee6a5c1df06363e5ede54
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.